Imagine leading a team that’s building an AI-powered healthcare app or a fintech solution that detects fraud in real time.
As a product manager with 10 years of experience, I’ve seen the field transform. Not long ago, product management was about web and mobile features; today, AI projects are the new frontier.
The journey to become a product manager for AI projects is challenging but incredibly rewarding, with opportunities spanning SaaS startups, hospitals, and fintech innovators. In this article, we’ll explore how you can ride this wave – from the skills you need to the steps to get started, all while leveraging resources like Refonte Learning to accelerate your growth.
The Rise of AI Product Management
AI is no longer a niche technology – it’s everywhere. Companies in software-as-a-service (SaaS), healthcare, and fintech are racing to infuse AI into their products to stay competitive. This has created a surge in demand for product managers who understand AI. In fact, AI is revolutionizing entire industries, and businesses are scrambling to keep up.
The role of AI product managers is at the forefront of this shift, with more than 14,000 job openings globally as of October 2023 (nearly 6,900 in the U.S. alone). These roles span far beyond Big Tech – industries like healthcare, finance, and retail are all jumping on the AI bandwagon, creating a diverse and rapidly expanding job market.
Why this sudden demand? One reason is that building AI-driven products has become more feasible. As Andrew Ng (co-founder of Coursera) noted, writing software – especially prototypes – is becoming cheaper and faster with AI. This means companies need more people who can decide what to build, not just engineers to build it. In other words, AI product management has a bright future, because if AI can speed up development, someone still needs to guide what the AI should create and why. Product managers fill that gap by understanding customer needs, business strategy, and technological possibilities.
This is reflected in how organizations are hiring and paying AI-savvy product managers. Salaries are soaring to match the demand – in the U.S., AI product managers earn an average of $133,600 annually, climbing to $200,000 for senior roles. High-demand sectors like SaaS, healthcare, and fintech are willing to invest in talent that can bridge the worlds of AI technology and customer experience. Healthcare AI is booming (the global AI in healthcare market was estimated at $19.27 billion in 2023, growing ~38% annually toward 2030), creating roles for PMs who can navigate medical regulations and AI capabilities. Fintech is similarly explosive (AI in fintech is expected to reach $18.3 billion by 2025), as banks and startups seek product managers to develop AI-driven fraud detection, risk management, and personalized banking products. And in the SaaS world, virtually every B2B software company is exploring AI features – whether it’s smarter analytics, automation, or AI-powered customer support – to add value for their users.
If you aim to become a product manager for AI projects, now is the perfect time. The market needs professionals who can ask the right questions: What AI solution will truly solve a user problem? How do we implement it responsibly? How do we measure success? Let’s delve into what the role entails and how you can prepare yourself to land it.
What Does an AI Product Manager Do?
At its core, an AI product manager is still a product manager – you own the product’s vision, strategy, and execution. But AI projects have unique twists that make this role distinct. You’re the bridge between cutting-edge technology and real customer needs. That means you must speak two languages: one of business and users, and one of data science and engineering.
Key responsibilities of product managers for AI projects include:
Defining the product strategy: You translate business goals into an AI product vision. For example, if you’re in healthcare, you might define how an AI diagnostic tool should improve patient outcomes or reduce costs.
Managing cross-functional teams: You work daily with data scientists, machine learning engineers, and software developers, as well as designers and domain experts. You don’t need to code the AI models yourself, but you do need to understand what’s possible. This involves coordinating efforts so that the AI development (like training an ML model) aligns with user interface design and business timelines.
Prioritizing features and data: AI products often require choosing the right features to build and the right data to use. You might decide whether to prioritize a new AI feature (say, a recommendation engine) versus improving an existing one, based on user impact and technical feasibility.
Ensuring ethical and effective AI: Crucially, AI product managers must consider ethics, privacy, and bias. If your AI is making decisions (like approving a loan or diagnosing an illness), you need to ensure fairness and transparency. This means working with your team to prevent biased outcomes and comply with regulations.
Continuous training and iteration: Unlike static software, AI systems learn and evolve. As a PM, you monitor model performance and user feedback, then iterate. If the AI isn’t accurate enough or users don’t trust it, it’s your job to tweak the strategy – maybe gather more data, adjust the algorithm (through your team), or improve user onboarding to set better expectations.
In short, AI product management blends classic product skills (user research, requirement definition, agile project management) with a strong understanding of AI technology. One AI product manager described their job as ensuring AI solutions actually deliver business impact by solving the most important customer problems. It’s one thing to develop a fancy machine learning model; it’s another to integrate it into a product that people find valuable and easy to use. Your mission is to make sure the AI isn’t just “cool” but actually meaningful to your target users.
Skills You Need to Manage AI Projects
How do you become that bridge between AI tech and user value? You’ll need to cultivate a blend of technical knowledge, business acumen, and interpersonal skills. Here are some key skills and qualities for an AI product manager:
AI/ML Literacy: You don’t need a PhD in machine learning, but you should understand the basics of how AI models work. Know common terms like training data, algorithm, model accuracy, NLP (Natural Language Processing), and Neural Networks. This helps you communicate with your technical team and make informed decisions. For instance, if the data science team says the model’s precision is 85%, you should grasp what that implies for users. Understanding machine learning algorithms and data pipelines is essential to guide the team and set realistic expectations.
Domain Expertise: Since AI is applied in contexts like healthcare, finance, or SaaS, having knowledge of the domain you’re working in is a huge plus. If you’re building an AI product for healthcare, understanding clinical workflows and regulations (like HIPAA) will help you make better decisions. For fintech, knowledge of banking or insurance processes will guide your AI product to fit industry needs. Many successful AI product managers actually come from the industry domain (e.g., a nurse or a financial analyst who moved into product management) because they understand the problems that need solving.
Data-Driven Decision Making: Product management has always required comfort with data, but with AI projects this goes double. You’ll be dealing with datasets to train models and metrics to evaluate them. You should be comfortable defining metrics like precision, recall, or A/B test results, and analyzing user interaction data. Being “data-driven” isn’t just a buzzword – it’s critical when you’re managing a product whose core function is learning from data.
User Experience and Empathy: AI can be complex and even scary to users. A top skill for AI PMs is translating complexity into a great user experience. Think about how to build user trust in AI. This could mean designing clear explanations for AI decisions (for example, showing why the AI recommended a certain action) or providing fallback options if the AI gets something wrong. Always empathize with users: if the AI makes a mistake, how does it affect them, and how can your product mitigate any negative effects?
Agile and Iterative Development: AI products often require experimentation. You might build a quick prototype model to see if an idea is feasible, then iterate. Familiarity with agile project management helps you handle this iterative cycle. You’ll plan sprints where maybe one sprint is about getting a model to a certain accuracy, the next is about integrating it into the app. Flexibility is key – sometimes the AI’s progress will be unpredictable, and you’ll need to adjust your roadmap.
Communication and Leadership: As with any PM role, soft skills are huge. You’ll be communicating across technical and non-technical stakeholders. One moment you’re explaining to the CEO why your AI-driven feature will drive business growth; the next, you’re in the weeds with engineers deciding how to handle a data issue. Great AI PMs can translate between “AI-speak” and “business-speak.” They also inspire and coordinate the team – setting a vision for how this AI will make a difference, and keeping everyone aligned to reach it.
Ethics and Responsibility: Being aware of ethical AI practices is increasingly important. You should be the voice in the room asking, “Is our AI treating all users fairly? Are we respecting privacy and consent with the data we use?” Especially in regulated fields like healthcare or finance, demonstrating knowledge of compliance (GDPR, FDA guidelines, etc.) is critical. Companies will rely on you to ensure the AI product doesn’t cross legal or moral lines.
If this list seems extensive, don’t be discouraged. You don’t need to be an expert in everything from day one. Many of these skills can be learned on the job or through targeted upskilling (which we’ll cover soon). The key is to identify which skills you already have from your current or past experience, and which you need to build. For example, if you’re already a software product manager, you likely have agile and communication skills; you might focus on learning more AI technical basics. If you come from a data science background, you might need to bolster your user experience and business strategy know-how.
Next, let’s talk about actionable steps to actually break into this role.
How to Become a Product Manager for AI Projects
Transitioning into AI product management or starting a career as an AI PM might feel daunting, but you can absolutely make it happen with a structured plan. Here’s a step-by-step guide to get you started on the path to become a product manager for AI projects:
Lay the Technical Foundation in AI: Begin by educating yourself on AI and machine learning fundamentals. This could mean taking an online course on AI for beginners or data science. Understand key concepts like how algorithms learn from data, what training vs. inference means, and the basics of data analytics. You don’t have to become a data scientist, but you should be able to comfortably discuss AI concepts. Plenty of resources exist – from free YouTube tutorials to formal courses. Refonte Learning, for instance, offers a Data Science & AI program that can give you a solid grounding in machine learning techniques and how they apply in real business scenarios. A strong foundation will help you later communicate with technical teams and also spot opportunities where AI can add value.
Strengthen Your Product Management Fundamentals: If you’re new to product management, simultaneously build the core PM skill set. Learn about product lifecycle, roadmap planning, writing product requirements, and user research methods. If you’re already a PM, identify the gaps in your experience relevant to AI projects. Perhaps get familiar with agile development if you haven’t practiced it deeply, or learn more about metrics and A/B testing for data-driven decisions. Consider a course or certification in product management or related areas. Refonte Learning’s courses in Project Management or even their Product Owner program can be great for mastering the frameworks and tools that product managers use daily. What you want is to be fluent in the process of product management – because you’ll apply those same processes to AI projects, just with a twist in content.
Get Hands-On with AI Projects: Theory and courses are essential, but nothing beats real experience. Look for opportunities to participate in AI-related projects, even in a small way. If you’re currently working at a company, see if you can get involved with an AI initiative internally – perhaps as the team’s product or project lead. If that’s not available, create your own experience: team up with a developer friend to build a simple AI-driven app, or contribute to an open-source AI project in a product role. You could also join hackathons or online competitions (Kaggle, for example) to work with AI data and problems. The goal is to apply your skills in a practical setting and build some proof of experience. This is also where Refonte Learning can help through their virtual internship programs. Refonte offers immersive global training and even internships, where you collaborate on projects with professionals around the world. Imagine working on a real AI project as part of a course – it’s a powerful way to gain experience for your resume and talking points for interviews.
Develop a Portfolio and Success Stories: As you gain experience from step 3, document it. Build a small portfolio that highlights your contributions to any AI-related project. It could be a slide deck, a case study, or a Medium blog post you write about the experience. For example, you might detail how you helped define requirements for a machine learning model or how you improved an AI feature based on user feedback. These stories demonstrate your capability. Hiring managers love to see candidates who not only have knowledge, but have applied it to solve problems. If you lack formal job experience in AI, a well-crafted side project can make a big impression – it shows initiative and practical understanding.
Show Domain Passion (SaaS, Healthcare, Fintech, etc.): Tailor your journey toward the industry that interests you most, as this can be your differentiator. If you have a passion for healthcare, dive into how AI is used in healthcare (read articles, follow influencers in that space). Likewise for fintech or SaaS. You want to come off as someone genuinely excited and informed about how AI is changing that industry. This domain knowledge, combined with AI and PM skills, makes you very attractive to employers in that sector. They’ll see that you “get” their world. For instance, talk about how you understand the challenges of doctors trusting AI diagnoses if you’re interviewing for a health tech PM role, or discuss the importance of data privacy in fintech AI products when pursuing a fintech PM role. Showing you understand the industry context is huge.
Network and Learn from Others: Breaking into any new field is easier when you connect with people already in it. Join communities or forums for product managers in AI. LinkedIn and Meetup groups are great places to start – look for events or webinars on AI product management. Don’t be shy about reaching out to AI product managers on LinkedIn for informational interviews; many are happy to share advice. Engage in discussions on platforms like Quora or Reddit where AI PMs hang out. (In fact, a Reddit poll of aspiring AI PMs revealed that nearly half were searching for effective resources to learn the skills– showing you’re not alone and that community knowledge-sharing is valuable.) By networking, you might find a mentor or simply gather insights on what companies are looking for. Sometimes job opportunities also arise through these connections, not just job postings.
Leverage Certifications and Education Credentials: While hands-on ability matters most, having certifications or recognized courses in your resume can help you get noticed, especially if you’re pivoting from a different field. Completing a reputable course like the AI Product Management course from Refonte Learning (or similar programs) signals to employers that you’ve invested in your professional development. Highlight any such certifications on your LinkedIn and resume. They can sometimes be conversation starters in interviews (“I see you took the Refonte Learning AI course – how was that?”). Be ready to discuss what you learned and how you applied it.
Prepare to Articulate Your Vision and Value: Finally, as you start applying to AI product manager roles, prepare your narrative. Be ready to answer: “Why do you want to manage AI products?” and “What makes you a good fit, given your background?” Perhaps your answer is that you have always been fascinated by technology and solving problems, and after 5 years in marketing (for example) you taught yourself AI basics and led a project that got you hooked on the power of machine learning to improve user experience. Whatever your story, frame it as a strength – your unique mix of experience (maybe domain expertise in finance, plus a newly acquired data science skillset, plus existing PM skills) is exactly what will help you succeed in that role. Show enthusiasm for continuous learning because this field changes fast. Employers in AI want to know you can adapt as the tech evolves.
Following these steps, you’ll gradually build the competence and confidence needed to transition into AI product management. Action and consistency are key – a little progress each day in learning or networking can snowball over a few months. I’ve seen mid-career professionals go from zero AI background to landing AI PM roles in under a year by being systematic and proactive.
High-Demand Industries and Opportunities
Let’s zoom in on the industries we’ve been mentioning – SaaS, healthcare, and fintech – and why they are hot spots for aspiring AI product managers. Understanding the landscape of these fields will help you target your efforts and see where you might fit best.
AI in SaaS (Software-as-a-Service): SaaS companies provide software over the cloud to businesses and consumers, and they are in a constant race to offer smarter, more efficient solutions. AI is being leveraged in SaaS for things like automated customer support (chatbots), predictive analytics dashboards, intelligent CRM features, and more. For example, an AI-powered SaaS tool might analyze user behavior to suggest optimal ways to use the product (think of productivity apps that suggest tips, or marketing software that predicts the best time to send emails). As a product manager in a SaaS company, you could be working on integrating a new AI feature that differentiates your product in the market. The challenge here is often choosing the right AI use-cases that deliver clear value to a wide user base. The opportunity is that SaaS companies often iterate quickly and are open to experimenting with AI – meaning you can drive innovation. Plus, many SaaS businesses are startups or scale-ups; they may be more willing to give someone with an unconventional background a shot if you demonstrate knowledge and passion.
AI in Healthcare: Healthcare is being transformed by AI, from diagnostic algorithms that read MRI scans to predictive models that improve patient care workflows. It’s a sector with massive stakes – successful AI products can literally save lives or significantly reduce costs for hospitals. As the market data showed, healthcare AI is growing at an astounding rate, fueled by the need for efficiency and better outcomes. As a product manager in this domain, you might work on products like AI systems that assist doctors in diagnosis, personalized medicine apps that tailor treatment plans using machine learning, or operational tools that streamline hospital logistics. You will need to balance innovation with caution, given heavy regulation and the critical nature of decisions. High-demand roles include AI product managers for medical devices, healthcare data platforms, and telehealth services using AI. If you have any background in life sciences or medical fields, this is a great domain to leverage that expertise. Refonte Learning and similar platforms often feature case studies or modules on healthcare AI, which could be valuable if you’re targeting this field. The impact you can have here is huge – it’s one of the most rewarding areas to apply AI if you’re passionate about helping people through technology.
AI in Fintech and Finance: Finance was early to adopt AI for things like algorithmic trading and fraud detection. Now, fintech startups and traditional banks alike are pushing into AI for loan approvals, credit scoring with alternative data, personalized financial advice (robo-advisors), and customer service automation. The fintech AI market is on a strong growth trajectory, reflecting how much these institutions are investing in AI capabilities. As a PM in fintech, you might find yourself working on a mobile banking app that uses AI to give users insights into their spending habits, or a platform that uses machine learning to detect suspicious transactions before they become fraud. Security and accuracy are paramount – nobody wants an AI that mistakenly flags legitimate transactions or, worse, overlooks fraud. A big focus area now is AI for fraud and risk management (as noted by industry reports projecting multi-billion growth driven by these use cases). If you come from a finance background or even just have a keen interest in financial services, highlight that. Fintech companies will value a PM who understands the complexities of financial regulations and customer trust, in addition to AI. Keep in mind, fintech often crosses into InsurTech and RegTech – adjacent fields using AI to improve insurance and regulatory compliance processes – which are also experiencing growth and need product leadership.
In all these industries, one theme stands out: upskilling and continuous learning are necessary to stay ahead. Because AI is a fast-evolving field, even once you land a product manager role, you’ll need to keep learning about new AI techniques (like the latest in deep learning or new AI regulations). The good news is that the same resources that helped you get into the role will continue to support you. Engaging with Refonte Learning courses or similar e-learning programs isn’t a one-time affair; it’s a way to ensure you remain at the cutting edge. Refonte’s community and webinars can keep you updated on trends (for example, how generative AI like GPT is being applied in product management, which was a hot topic in recent years).
A product manager collaborates with her team to map out features for an AI project. Effective communication and cross-functional teamwork are crucial when managing AI products, as you’ll be aligning data scientists, engineers, designers, and business stakeholders toward a common goal. In high-demand industries like SaaS and healthcare, these brainstorming sessions help ensure that the AI solutions being developed truly address user needs and regulatory requirements.
Upskilling with Refonte Learning: Your Career Catalyst
By now, you might be thinking: This is a lot to learn and do. And it is – transitioning into a cutting-edge field like AI product management is a significant endeavor. But you don’t have to do it alone or figure out everything from scratch. This is where leveraging structured programs and courses can dramatically accelerate your journey. Refonte Learning is one of the leading platforms that can support you every step of the way.
Refonte Learning stands out by embracing a philosophy of learning through practical application. What does that mean for you? It means their courses are not just lectures and theory. They emphasize hands-on experience, engaging you in real projects so you can apply what you learn in real-time. For an aspiring AI product manager, this approach is gold. Instead of just reading about how to gather requirements for an AI product, you might actually collaborate in a simulated project to do it. Rather than just watching videos on machine learning, you could be tasked with working alongside a mentor to define an AI model’s success criteria for a case study product.
Here are some ways Refonte Learning’s courses and programs can benefit someone looking to upskill in AI and product management:
Comprehensive Curriculum Covering AI and PM: Refonte offers a range of programs, from Data Science & AI to Project Management and even niche areas like AI Engineering and Prompt Engineering. For an AI product manager track, you could mix and match – for instance, start with the Data Science & AI program to solidify your technical understanding, then take a Product Owner or Project Management course to round out your product skills. The content is up-to-date with the latest trends (they even have a Discover ChatGPT Masterclass, indicating they cover current AI advancements). So you’re learning industry-relevant material, not outdated case studies.
Expert-Led and Mentor-Supported: With a decade in the industry, I can confidently say mentors make a huge difference. Refonte’s programs are expert-led, meaning you learn from instructors who have real-world experience. They also have a network of academic staff and mentors. This is an opportunity to get feedback on your ideas and guidance on your career questions. Let’s say you’re unsure how to present your non-AI past experience as a strength – a mentor from Refonte can help you frame that narrative or give you mock product scenarios to build confidence.
Virtual Internships and Real Projects: One feature that sets Refonte Learning apart is their Refonte International Training & Internship Program (RITIP), which connects learners to virtual internships. Imagine being able to say in your interview, “I recently completed an internship where I acted as an Associate Product Manager for an AI project in the healthcare sector, as part of my Refonte Learning program.” That’s a concrete experience which can make you stand out. During these projects, you’ll collaborate with people from different parts of the world (since it’s a global program), mirroring the cross-functional teamwork you’ll do on the job. It’s practical and also helps you build a professional network. Many of Refonte’s past students talk about how working on real deliverables boosted their confidence significantly. It’s not just textbook learning – you build something.
Flexibility for Working Professionals: If you’re a mid-career switcher, you likely have a job and maybe a family or other responsibilities. Refonte’s courses are designed with flexibility in mind – often online and self-paced or with convenient scheduling. This means you can upskill without quitting your day job. The ability to learn at your own pace is crucial when tackling a complex field like AI; you might need to re-watch a module on neural networks or spend extra time on a project phase, and that’s okay. The platform structure supports it.
Career Services and Community: Beyond coursework, Refonte Learning offers community support (they have a network of Refonte alumni and matched candidates). Being part of this community means you can exchange tips, get moral support, and even hear about job openings. Some e-learning platforms also provide resume reviews or career coaching. Refonte’s focus on “Your evolution from learner to business authority” suggests they are keen on helping learners translate new skills into career advancement. In practical terms, they might help you with interview prep or connect you with partner companies looking for talent. Knowing that Refonte Learning has helped over 3,500 students globally to upskill in tech fields (with 4.5+ years of expertise in this space) adds confidence that their ecosystem is robust and well-connected.
Now, I want to clarify that no course or certification will magically make you an AI product manager. Your initiative and how you leverage these tools matter most. But a platform like Refonte Learning acts as a catalyst. It can compress your learning timeline, fill knowledge gaps, and provide credibility to your profile. It’s a bit like having a gym and personal trainer when getting in shape – you still do the hard work, but you have guidance and a structured plan to follow, which improves your results.
As someone who has also been involved in hiring, I can tell you that seeing Refonte Learning on a candidate’s resume is increasingly common and positively viewed, especially if accompanied by a clear description of projects completed. It shows me the candidate is serious about upskilling and likely has practical know-how.
In summary, consider making Refonte Learning or a similar upskilling partner a core part of your journey. The investment you make in learning will pay off when you can confidently step into an interview or a new job role, already fluent in the language of AI and product management. The field is moving fast, and this is an efficient way to stay current. Remember the Reddit poll we mentioned: many aspiring AI PMs are struggling to find effective resources. By choosing a well-structured learning path, you’re giving yourself a significant advantage.
Conclusion: Embrace the Journey and Shape the Future
Stepping into the role of an AI product manager is more than just a career move – it’s joining the forefront of technological innovation. It’s a role where you could be shaping how AI enhances peoples’ lives: making software more intuitive, healthcare more proactive, and finance more inclusive. The road to get there involves dedication to learning and personal growth. But as we’ve explored, the path is clear and attainable, even if you’re a mid-career professional or coming from a different background.
Let’s recap the key takeaways for becoming a product manager for AI projects:
Demand is on Your Side: The need for AI-savvy product managers is booming across industries. Companies are actively looking for people who can translate AI potential into real product value. This demand spans SaaS, healthcare, fintech, and beyond – so you have options to pursue what genuinely interests you. High salaries and abundant opportunities reflect this trend, making it a promising and lucrative career direction.
Blend Your Unique Skills with New Ones: You likely already have valuable experience – whether it’s in project management, engineering, design, or a specific industry. Don’t throw that away. Instead, augment it with AI knowledge and product management techniques. The combination of what you bring and what you learn will shape you into a distinctive candidate. Continuous learning is your friend; even once you land the role, keep sharpening your saw with the latest AI and product insights.
Take Action with Structured Learning: Use resources like Refonte Learning to accelerate your progress. A structured course can give you a roadmap, while hands-on projects build real confidence. It’s a smart shortcut to gain experience that would otherwise take years of trial and error. And remember, you’re investing in yourself. Each new skill or project you complete is not just a line on a resume – it’s a tool you’ll use to build products and solve problems in the real world. Refonte’s training, with its practical approach and mentorship, can be the launchpad that propels you into that first AI PM job.
Network and Stay Curious: The field of AI product management is evolving as we speak. Stay curious and connected. Subscribe to industry newsletters, follow thought leaders on LinkedIn, attend webinars or local meetups. Communities can often alert you to emerging trends (like a new AI tool that product managers are adopting, or a discussion on AI ethics that sparks ideas for your product). This not only helps you stay current, but also continuously feeds your passion – and passion is something you cannot fake. It’s evident when you truly find this work engaging, and that enthusiasm will carry you through challenges and impress others.
Finally, embrace the mindset of an explorer. Becoming a product manager for AI projects means you’ll often tread into uncharted territory – maybe your team is implementing an AI technique that’s never been used before in your company, or you’re defining best practices where none existed. This is part of the thrill. Your 10-year veteran author here can attest: the projects that felt like brave new worlds were the ones that taught me the most and were most satisfying in the end.
As you take your next steps, envision the impact you want to have. Perhaps a year from now, you’ll be launching an AI-powered product feature that wows users, or leading strategy for an AI platform in an industry you love. That vision is within reach if you start preparing today. The combination of market opportunity, accessible learning resources, and your determination forms the perfect convergence for success.
So go ahead – take that first course, reach out to that mentor, write down that AI product idea you’ve been mulling over. Each action is a step closer to your goal. The world of AI projects needs skilled product managers like you to guide the next wave of innovation. With a practical plan and the support of programs like Refonte Learning, you’re not just aiming for a new job – you’re gearing up to lead exciting projects that could shape the future of technology.