Product Engineer

Job Title

Software Development Engineer

Requirements

Must-haves:

• 5+ years of software development experience
• Experience owning at least one system in production
• Experience with React, Next.js
• Experience with Node.js
• Experience with Python
• Experience with Postgres
• Experience with AWS, including regulated or restricted environments requiring self-hosted services
• Experience building LLM applications (e.g., tool-using agents, retrieval and reranking, context management, long-running sessions)
• Experience evaluating AI systems (e.g., deterministic checks, LLM judges, threshold calibration)
• Experience with DevOps practices (e.g., CI/CD pipelines, containerization, infrastructure as code with Docker, Terraform, Pulumi, SST, etc.)
• Experience shipping products that real users rely on, with a clear account of post-launch outcomes
• Proficiency with AI-assisted development workflows (e.g., Claude Code) and informed views on their strengths and limits
• Ability to make UX and product calls on problems that arrive without a spec or a mockup
• Ability to tell a broken evaluation harness apart from an underperforming model
• Deep knowledge of production-grade system design and the failure modes that surface at scale
• Deep understanding of system-wide visibility (e.g., cloud services, security, service dependencies, observability)
• Strong communication skills in both spoken and written English

Nice-to-haves:

• Startup experience
• Experience designing, building, and operating MCP servers
• Experience with regulated cloud environments (e.g. AWS GovCloud)
• Experience with data pipelines or ML infrastructure
• Experience with multi-tenant or whitelabeled products
• Background in workforce development or edtech platforms
• Bachelor's Degree in Computer Engineering, Computer Science, or equivalent

What You Will Work On

• Own the architecture of your domain end to end: data modeling, API design, cloud infrastructure, and CI/CD
• Build and release full-stack features spanning front-end, back-end, and infrastructure
• Develop production AI agents with sessions that stay open for weeks, per-turn context assembly, database-writing tool calls, persistent memory, and runtime redirection by non-engineers without code changes
• Expand the evaluation systems that track whether those agents improve or regress, keeping the harness trustworthy enough for the metrics to carry meaning
• Develop hybrid matching and search: parallel sparse and dense retrieval, reranking, recency handling, and looping real usage signals back into scoring
• Create the interfaces layered on top: streaming chat surfaces, admin and operator consoles, and several whitelabeled deployments delivered from one build
• Own the DevOps lifecycle: containerization, deployment pipelines, monitoring, and cloud environments, including one regulated setup where third-party APIs are off-limits
• Design, ship, and run MCP servers to integrate legacy systems and gradually retire them
• Define and enforce standards for code quality, security, performance, and tenant isolation in a SOC 2 Type 2 certified environment where certain deployments face stricter requirements
• Partner with product and leadership on build-vs-buy calls, technical risk, and architectural direction
• Stay connected to the people using the product and own whether the work actually landed
• Our Stack: TypeScript, Next.js, React, tRPC, Postgres with Drizzle, Tailwind and a shadcn-based design system, Python, AWS, Pulumi, SST, Docker, Qdrant, Bedrock, Turborepo, pnpm, Vitest, Playwright