Scaling individual impact: Insights from an AI engineering leader

Traditionally, moving up in an organization has meant leading increasingly large teams of people, with all the business and operational duties that entails. As a leader of large teams, your contributions can become less about your own work and more about your team’s output and impact. There’s another path, though. The rapidly evolving fields of artificial intelligence (AI) and machine learning (ML) have increased demand for engineering leaders who drive impact as individual contributors (ICs). An IC has more flexibility to move across different parts of the organization, solve problems that require expertise from different technical domains, and keep their skill set aligned with the latest developments (hopefully with the added benefit of fewer meetings).

In an executive IC role as a technical leader, I have a deep impact by looking at the intersections of systems across organizational boundaries, prioritize the problems that really need solving, then assemble stakeholders from across teams to create the best solutions.

Driving influence through expertise

People leaders typically have the benefit of an organization that scales with them. As an IC, you scale through the scope, complexity, and impact of the problems you help solve. The key to being effective is getting really good at identifying and structuring problems. You need to proactively identify the most impactful problems to solve—the ones that deliver the most value but that others aren’t focusing on—and structure them in a way that makes them easier to solve.

People skills are still important because building strong relationships with colleagues is fundamental. When consensus is clear, solving problems is straightforward, but when the solution challenges the status quo, it’s crucial to have established technical credibility and organizational influence.

And then there’s the fun part: getting your hands dirty. Choosing the IC path has allowed me to spend more time designing and building AI/ML systems than other management roles would—prototyping, experimenting with new tools and techniques, and thinking deeply about our most complex technical challenges.

A great example I’ve been fortunate to work on involved designing the structure of a new ML-driven platform. It required significant knowledge at the cutting edge and touched multiple other parts of the organization. The freedom to structure my time as an IC allowed me to dive deep in the domain, understand the technical needs of the problem space, and scope the approach. At the same time, I worked across multiple enterprise and line-of-business teams to align appropriate resources and define solutions that met the business needs of our partners. This allowed us to deliver a cutting-edge solution on a very short timescale to help the organization safely scale a new set of capabilities.

Being an IC lets you operate more like a surgeon than a general. You focus your efforts on precise, high-leverage interventions. Rapid, iterative problem-solving is what makes the role impactful and rewarding.

The keys to success as an IC executive

In an IC executive role, there are key skills that are essential. First is maintaining deep technical expertise. I usually have a couple of different lines of study going on at any given time, one that’s closely related to the problems I’m currently working on, and another that takes a long view on foundational knowledge that will help me in the future.

Second is the ability to proactively identify and structure high-impact problems. That means developing a strong intuition for where AI/ML can drive the most business value, and leveraging the problem in a way that achieves the highest business results.

Determining how the problem will be formulated means considering what specific problem you are trying to solve and what you are leaving off the table. This intentional approach aligns the right complexity level to the problem to meet the organization’s needs with the minimum level of effort. The next step is breaking down the problem into chunks that can be solved by the people or teams aligned to the effort.

Doing this well requires building a diverse network across the organization. Building and nurturing relationships in different functional areas is crucial to IC success, giving you the context to spot impactful problems and the influence to mobilize resources to address them.

Finally, you have to be an effective communicator who can translate between technical and business audiences. Executives need you to contextualize system design choices in terms of business outcomes and trade-offs. And engineers need you to provide crisp problem statements and solution sketches.

It’s a unique mix of skills, but if you can cultivate that combination of technical depth, organizational savvy, and business-conscious communication, ICs can drive powerful innovations. And you can do it while preserving the hands-on problem-solving abilities that likely drew you to engineering in the first place.

Empowering IC Career Paths

As the fields of AI/ML evolve, there’s a growing need for senior ICs who can provide technical leadership. Many organizations are realizing that they need people who can combine deep expertise with strategic thinking to ensure these technologies are being applied effectively.

However, many companies are still figuring out how to empower and support IC career paths. I’m fortunate that Capital One has invested heavily in creating a strong Distinguished Engineer community. We have mentorship, training, and knowledge-sharing structures in place to help senior ICs grow and drive innovation.

ICs have more freedom than most to craft their own job description around their own preferences and skill sets. Some ICs may choose to focus on hands-on coding, tackling deeply complex problems within an organization. Others may take a more holistic approach, examining how teams intersect and continually collaborating in different areas to advance projects. Either way, an IC needs to be able to see the organization from a broad perspective, and know how to spot the right places to focus their attention.

Effective ICs also need the space and resources to stay on the bleeding edge of their fields. In a domain like AI/ML that’s evolving so rapidly, continuous learning and exploration are essential. It’s not a nice-to-have feature, but a core part of the job, and since your time as an individual doesn’t scale, it requires dedication to time management.

Shaping the future

The role of an executive IC in engineering is all about combining deep technical expertise with a strategic mindset. That’s a key ingredient in the kind of transformational change that AI is driving, but realizing this potential will require a shift in the way many organizations think about leadership.

I’m excited to see more engineers pursue an IC path and bring their unique mix of skills to bear on the toughest challenges in AI/ML. With the right organizational support, I believe a new generation of IC leaders will emerge and help shape the future of the field. That’s the opportunity ahead of us, and I’m looking forward to leading by doing.

This content was produced by Capital One. It was not written by MIT Technology Review’s editorial staff.

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