Forward Deployed Engineer, Team Lead

About this role

ABOUT LUMINAI

Healthcare operations have always depended on people to bridge the gaps that technology couldn't. It relies on complex manual work to carry out critical internal processes, yet most health systems don’t have enough resources to properly automate these tasks, leaving them stuck in outdated, labor-intensive SOPs.

Luminai structures the chaos, automates the manual handoffs, and deploys end-to-end workflows across every system, providing the integrated intelligence layer to improve processes over time. By delegating to autonomous AI systems those mission-critical workflows that previously expended valuable human time, Luminai allows doctors and administrators to do what they do best: Focus on Patients.

We've raised $60M in funding, including our recent Series B led by Peak XV Partners (formerly Sequoia India), with participation from healthcare-focused Define Ventures and continued support from General Catalyst and Y Combinator. We're backed by some of the best investors in Silicon Valley, including Kevin Weil (Chief Product Officer at OpenAI), Arash Ferdowsi (co-founder of Dropbox), Katie Stanton (former VP Global Media, Twitter), and CEOs of companies such as Flexport, Notion, Front, Ramp, and Twitch.

Our team is in-office 4 days a week (Monday - Friday, Wednesday optional WFH) in either San Fransisco, California or New York, New York.

About the role

As a Forward Deployed Engineering Lead, you will sit at the intersection of engineering, product, and customer delivery, while also raising the bar for how the FDE team operates. You'll embed directly with customers, deeply understand their workflows, and design and deploy AI-powered solutions that deliver immediate, real-world impact, while also setting the technical standard for the team around you.

This is a highly autonomous, hands-on role for someone who thrives in ambiguous environments, enjoys working directly with customers, and wants to shape product direction through what they see in the field. You'll partner closely with Product and Engineering to turn customer needs into scalable systems that improve how healthcare organizations operate, and you'll bring the judgment of a more senior builder to a team that's still growing into that muscle.

What You'll Do

- Embed directly with customers to understand their workflows, constraints, and success criteria

- Design, build, and deploy AI-driven solutions tailored to real operational problems

- Build and maintain production systems including APIs, integrations, monitoring, and feedback loops

- Translate business requirements and customer needs into technical architectures and implementations

- Operate in high-stakes environments where reliability, speed, and judgment matter

- Identify patterns across customer deployments and feed insights back into core product and platform development

- Partner closely with Product and Engineering to influence roadmap, abstractions, and long-term system design

- Own deployments end-to-end, from initial scoping through launch and iteration

- Set technical direction and best practices for the FDE team, raising the bar on code quality, architecture decisions, and deployment rigor

- Mentor and unblock other FDEs, acting as a senior voice in the room on ambiguous technical and customer tradeoffs

What We're Looking For

- 5+ years of software engineering experience, ideally as an FDE or in backend / systems-focused work

- A track record of being the senior, steady hand on a team, comfortable operating with less oversight and setting the bar for others

- Strong proficiency in Python (TypeScript / JavaScript experience is a plus)

- Experience working with cloud infrastructure (AWS, GCP, or Azure)

- Ability to translate ambiguous requirements into working, production-ready systems

- Strong communication skills and comfort working with both technical and non-technical stakeholders

- High ownership mindset with the ability to operate independently in fast-changing environments

- Experience with AI systems (LLMs, vector databases, prompt engineering, or agent frameworks) is a strong plus

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