Senior AI Developer

Role Overview

• Own the architecture and evolution of the shared components, libraries, and platform capabilities the whole AI team builds on.
• Design and build the CI/CD patterns, deployment pipelines, observability tooling, and developer workflows that make shipping agents to production predictable and repeatable.
• Lead the team on AI tooling adoption—coding assistants, agentic development workflows, evaluation frameworks.
• Carry work from requirements shaping and solution design through deployment, monitoring, and iteration.
• Articulate a clear engineering direction to your team and to stakeholders. Translate ambiguous problems into concrete plans.
• Actively grow the engineers around you. Run technical reviews, establish best practices, and create an environment where the team can move quickly—without constantly second-guessing their decisions.

Requirements

• 7+ years of hands-on software development, with deep proficiency in at least one modern backend or full-stack language and breadth across the full SDLC
• Strong AWS experience—fluent with Lambda, ECS, S3, RDS, API Gateway, and CloudWatch; able to design production-grade cloud-native architectures that are observable and operationally sound
• Deep grasp of SaaS architecture principles—you design systems others build on top of, and you understand the tradeoffs between speed, scalability, and maintainability at each layer
• Proven track record building developer platforms and delivery systems—CI/CD pipelines, deployment automation, testing frameworks, and the processes that let teams ship AI features rapidly and safely
• Expert-level understanding of agentic system design: orchestration, tool use, memory, retrieval, evaluation, and agent-to-agent communication—with the judgment to make the right architectural calls under real constraints
• Hands-on experience with production agentic tooling—orchestration frameworks (LangChain, LangGraph, CrewAI), LLM APIs (OpenAI, Anthropic, Bedrock), vector databases (Pinecone, Weaviate, pgvector), and evaluation/observability platforms (LangSmith, PromptLayer)
• Demonstrated experience delivering production, client-facing agentic solutions end-to-end—you’ve shipped agents real users depend on, navigated the hard operational problems, and iterated from prototype to stable production
• Strong understanding of database design and data persistence fundamentals (relational or document stores)

Tech Stack

• AWS
• Cloud
• SDLC

Benefits

• Competitive wages
• Wellness days
• Community Engagement Committee
• Flexible workday
• Benefits Ask us for a copy of our health and dental benefits!
• Culture committee