1 month ago
Responsibilities
- Perform the customer’s operational job for two to four weeks to understand its constraints and workflows firsthand.
- Become fluent in unfamiliar business domains and redesign functions from first principles with operators and Forward Deployed Executives.
- Build and ship production GenAI systems, including LLM applications, agentic workflows, retrieval and structured-extraction pipelines, backend services, data pipelines, and AI layers.
- Create evaluation harnesses, define measurable success criteria, instrument systems, and use evaluations to guide product design.
- Write production code across the stack, primarily using Python and TypeScript.
- Deploy containerized, observable, and maintainable systems to AWS or other customer-required cloud environments.
- Feed lessons from customer engagements back into the company’s reusable industry blueprints.
- Drive adoption, shape commitments before delivery, and own outcomes tied to business-unit KPIs.
- Communicate credibly with customer operators, engineers, executives, CTOs, and business-unit leaders.
Requirements
- 8+ years of software-building experience, including substantial accountability for production code.
- Current hands-on engineering ability and willingness to remain in an individual-contributor coding role.
- Willingness to spend weeks performing an operator’s job before writing code.
- Ability to quickly learn unfamiliar business domains and challenge established processes constructively.
- Production experience shipping GenAI or LLM systems beyond demos and notebooks.
- Experience building or owning evaluation suites for non-deterministic systems.
- Strong engineering fundamentals and the ability to become productive in unfamiliar codebases or languages.
- Proficiency in Python and/or TypeScript.
- Cloud-native delivery experience on AWS, including containers, Kubernetes or ECS, infrastructure as code, and operational ownership.
- Ability to work credibly with senior business and technical stakeholders in redesign and scoping conversations.
- Strong ownership, comfort with ambiguity, and ability to work autonomously.
- Solid AI/ML foundations and ability to reason about model failure modes.
- Strong hands-on production experience with Claude Code and Cowork.
- Fluent written and spoken English.
- Preferred qualifications include experience as a founder, CTO, or engineering leader; depth in financial services, insurance, healthcare, or asset management; consulting or embedded customer delivery experience; data-platform expertise; MLOps and classical ML experience; fine-tuning or inference optimization experience; graph-database experience; infrastructure-as-code depth; and open-source contributions or public writing on applied AI.
Benefits
- Frontier delivery work across Cowork Activation, Agentic SDLC, and Blueprint Activations in financial services and healthcare.
- Opportunity to shape enterprise AI adoption from strategy through first deployment.
- Work in small, senior teams alongside Principal Architects and Forward Deployed Engineers.
- Opportunity to build AI delivery tooling and frameworks rather than only use them.
- Remote-friendly culture.
- Hiring process includes an introductory conversation, two live engineering sessions, a redesign session, and a team and practice conversation.
Tech Stack
Categories
Forward Deployed
