Applied AI Engineer - Manager

Percepta•New York, NY

45d•$250,000 - $425,000•Hybrid

About The Position

Percepta's mission is to transform critical institutions with applied AI, focusing on industries like healthcare, manufacturing, and energy. They achieve this by embedding with industry-leading customers to drive AI transformation, leveraging forward-deployed expertise in engineering, product, and research, their in-house toolkit called Mosaic, and strategic partnerships. The team consists of Applied AI Engineers, Embedded Product Managers, and Researchers motivated by diffusing AI's promise into tangible improvements. Percepta is a direct partnership with General Catalyst. This role is for a player-coach Engineering Manager to help grow engineers tackling complex customer problems. Applied AI Engineers embed directly with customer teams, owning delivery and shipping production AI systems in challenging environments. The manager will help scale the growth of these engineers by managing a small team, focusing on their development trajectory. This is a hands-on role where the manager will still be writing code, reviewing designs, and stepping in to ensure launches are successful. The role requires staying close to the work to understand the challenges engineers face when making architecture calls within unfamiliar enterprise systems. The balance between people management and technical contribution shifts based on project phases, with more focus on code during rollouts and more on people between rollouts. The manager will partner with an Engagement Lead on customer strategy and Growth Leads on engineer development, and will be a key voice in shaping the future of Mosaic based on field insights.

Requirements

7+ years building production software
At least 2 years leading or managing engineers (titles like TL are acceptable)
Still writes code and wants to continue writing code
Proficiency in Python and TypeScript
A track record of demonstrably improving engineers' performance through management
Strong systems taste, with the ability to explain design choices, potential strains, and trade-offs
Comfort operating in ambiguity and an instinct for exploring unfamiliar systems
Real product empathy, considering user adoption and workflow integration
Fluency with LLMs as an engineering surface (Agents, tools, context, evals, AI dev tooling)
Ability to be direct and kind, fostering trust through candor
Strong communication skills with non-technical stakeholders, leading with answers and caveats

Nice To Haves

Managed a team through a production launch within an enterprise environment
Experience with enterprise integrations (EHRs, ERPs, RCM, supply chain, workforce systems)
Domain depth in healthcare, energy, manufacturing, or financial services
Prior forward-deployed, consulting, or design partner work
Built tooling or frameworks used by multiple teams
Startup or founding engineer background

Responsibilities

Grow engineers deliberately, with a clear point of view on their current state and future potential, aligning their work with business needs and interests.
Ramp people properly by investing heavily upfront, understanding their learning and working styles, and providing context through pairing and co-attending customer meetings.
Give feedback in the moment, providing immediate, specific, and respectful feedback on design approaches or code quality.
Own the technical outcome for the team's workstreams, ensuring enough context to identify issues before they become crises.
Make the hard technical calls, acting as the final decision-maker on critical choices and documenting the reasoning.
Set the team's standards for code quality, testing, review rigor, and documentation.
Be credible with customers by owning the technical relationship through consistent delivery and insightful questions.
Feed field insights back into the product (Mosaic) by identifying patterns and pushing reusable components.
Participate in hiring by interviewing candidates and calibrating the interview process.