Senior AI Developer

We are seeking a talented Senior AI Developer to be a key participant in an ambitious AI transformation of a finance platform serving local and state government agencies. The team is raising the bar across the development process with an intentional agentic focus. This is an opportunity for an innovative and curious AI developer who wants to push the boundaries of what enterprise AI applications can do.

The goal is to build applications with AI capabilities from the ground up. We need developers who know what good looks like-not just in code, but across the considerations required to build and design enterprise-grade software.

You’ll own challenging problems: orchestration patterns that hold up under real-world load, developer experiences that let teammates move quickly with confidence, and engineering decisions that turn ambiguous requirements into concrete, operable systems.

Role Focus: We are looking for a strong platform/backend engineer with hands-on Agentic AI experience. The focus is on building scalable platforms and production AI systems, not only ML experimentation.

What You’ll Do

· Platform Ownership

Own the evolution of shared AI components, libraries, and platform capabilities the whole team builds on. Set the bar for reliability, testability, and developer experience by shipping production-ready solutions.

· AI Feature Development

Design and build AI-powered product features end-to-end, including LLM orchestration, prompt engineering workflows, evaluation, and observability. Carry work from requirements shaping through deployment, monitoring, and iteration.

· Delivery Systems

Design and build CI/CD patterns, deployment pipelines, observability tooling, and developer workflows that make shipping agents to production predictable and repeatable.

· AI Tooling Leadership

Lead the team on AI tooling adoption, including coding assistants, agentic development workflows, and evaluation frameworks. Establish patterns that give teammates meaningful leverage.

· Backend Platform Engineering

Build and optimize core SaaS platform systems that AI features depend on, including high-scale background processing, scalable APIs, ingestion pipelines, search and discovery, and PostgreSQL performance.

· Technical Vision

Articulate a clear engineering direction to the team and stakeholders. Translate ambiguous problems into concrete plans and build shared understanding across engineering and product.

· Mentorship & Growth

Actively grow engineers through technical reviews, best practices, and an environment where the team can move quickly without constantly second-guessing technical decisions.

The ideal candidate is a platform/backend engineer with strong Agentic AI experience and experience owning production systems and technical direction.

What You Bring

· 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.

· Understanding of agentic system design, including orchestration, tool use, memory, retrieval, evaluation, and agent-to-agent communication, with the judgment to make architectural decisions under real constraints.

· Hands-on experience with production agentic tooling such as LangChain, LangGraph, CrewAI, LLM APIs including OpenAI, Anthropic, or Bedrock, vector databases, and evaluation/observability platforms such as LangSmith or PromptLayer.

· Experience building scalable multi-tenant SaaS applications, ideally with C#, Ruby, Rails, Elixir, Python, or a similar language.

· Demonstrated experience delivering production, client-facing agentic solutions end-to-end, from prototype through stable production.

· Strong AWS experience, or similar experience on Azure, with familiarity with Lambda, ECS, S3, RDS, API Gateway, and CloudWatch and the ability to design observable, production-grade cloud-native architectures.

· Deep understanding of SaaS architecture principles and the tradeoffs between speed, scalability, and maintainability.

· Proven experience building developer platforms and delivery systems, including CI/CD pipelines, deployment automation, testing frameworks, and processes that enable teams to ship AI features rapidly and safely.

· Strong background in background processing systems, including Redis-backed job queues and schedulers, and high-scale data pipelines.

· Solid understanding of PostgreSQL schema design and performance optimization.

· Experience designing and operating production REST APIs, including authentication, versioning, and validation.

· Understanding of event-driven development.

· Experience with search and discovery systems, including full-text, semantic, or vector search.

· Strong understanding of security best practices, including authentication, data isolation, and secrets management.

· A demonstrated AI-first development approach, with concrete examples of using LLMs and agentic tools such as Claude Code, Cursor, or Copilot across daily engineering work.

Nice to Have

Experience in government technology, public sector, or another compliance-heavy domain, including auditability, data isolation, and security reviews.