The posting
About the role:
What you’ll do:
- 8+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way.
- You will take the operator’s seat. You are genuinely willing to spend weeks doing someone else’s job — claims processing, underwriting, revenue-cycle work — before you write a line of code. Engineers who need to stay in the IDE should not apply.
- You learn domains fast. Demonstrated ability to become conversant in an unfamiliar business function quickly enough to argue with the people who do it for a living.
- Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works.
- You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why.
- Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack.
- Cloud-native delivery on AWS (GCP/Azure a plus): containers, Kubernetes/ECS, IaC, CI/CD, and the operational reality of a system someone else inherits.
- Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room.
- Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job.
- Solid AI/ML foundations — you understand what the models do well enough to reason about failure modes, not just call the API.
- Strong hands-on prodcution experience with Claude Code/Cowork.
- Fluent English, written and spoken.
- Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution.
- Real depth in one of our blueprint industries: financial services, insurance, healthcare, asset management.
- Consulting, professional services, or other embedded customer-facing delivery.
- Data platform depth: data lakes, warehouses, streaming and real-time analytics, data mesh and data contracts, governance and data quality.
- MLOps and classical ML: PyTorch, SageMaker, MLflow.
- Fine-tuning, distillation, or inference/serving optimization.
- Graph databases (Neo4j, AWS Neptune).
- IaC depth: AWS CDK, CloudFormation, Terraform.
- Open-source contributions or public writing on applied AI.
What We Offer:
- Frontier delivery work across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare
- The chance to shape how leading enterprises adopt AI, from strategy through first deployment
- A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers
- A growing AI delivery practice where you help build the tooling and frameworks, not just use them
- Remote-friendly culture
- High-impact role with direct visibility to leadership
- Strong earning potential with performance-based bonuses
- Opportunity to work with cutting-edge AI and cloud solutions
- Unlimited Vacation policy
- Generous health, vision, and dental insurance
- 401(K) matching plan
- OTE range: up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, abilities of the applicant, and alignment with market data.
How we hire:
- Intro conversation — the role, your background, what you want to be doing.
- Two live engineering sessions. Real problems, your own editor. You may use an LLM assistant (ChatGPT, Claude) — how you work now includes these tools. Autocomplete/agentic coding tools are off for these sessions.
- The redesign session. We hand you an unfamiliar business function and the constraints of the person who performs it. You have to understand the job well enough to rebuild it — then say what you’d build and how you’d know it worked. No LLMs for this one.
- Team and practice conversation.
