Job Description
Signant Health is looking for a Software Engineer – AI Accelerated Development to build AI-powered, agentic features into our clinical trial platforms. Working across the .NET stack, you will take AI capabilities from backend LLM integration through to a usable front-end — designing agents and agentic workflows, not just prompting a model. This is a hands-on engineering role for someone who works with agentic tooling every day and wants to ship production AI in a regulated, high-impact environment. We weigh the depth of your AI and agentic build experience more heavily than years of general experience: a developer with one to three years of substantive, hands-on agentic work is exactly the profile we are targeting.
KEY ACCOUNTABILITIES – Function
- Design and build AI agents and agentic workflows — tool-use/function calling, multi-step task orchestration, and agent loops — that power Signant Health’s clinical trial platforms.
- Integrate LLM APIs (Anthropic, OpenAI, Bedrock, or Azure OpenAI) into .NET application code, handling authentication, streaming, error handling, and cost/latency tradeoffs.
- Deliver AI features end-to-end, taking them from backend integration through to a usable, production-ready front-end.
- Build custom agents and tools with the Claude Agent SDK, wiring and steering agent loops.
- Author custom skills and slash commands for Claude Code to codify team-specific workflows.
- Implement RAG pipelines and integrate vector stores (e.g. Qdrant, pgvector, Pinecone) to ground agent outputs in trusted data.
- Instrument agents for evaluation and observability so their outputs can be verified, measured, and audited.
- Apply AI-specific risk controls appropriate to a regulated clinical environment, addressing hallucination, determinism, and auditability of agent decisions.
- Use Claude Code (or an equivalent agentic CLI) daily as a primary development tool, reviewing and steering AI-generated diffs.
KNOWLEDGE, SKILLS & ATTRIBUTES
Essential:
- Full-stack .NET development — C#/ASP.NET Core on the backend paired with a modern front-end framework.
- Hands-on agentic development experience — building AI agents or agentic workflows (tool-use/function calling, multi-step task orchestration, agent loops); not just prompting an LLM, but building systems around one.
- Practical LLM API integration (Anthropic, OpenAI, Bedrock, or Azure OpenAI), including authentication, streaming, error handling, and cost/latency tradeoffs.
- Proven full-stack delivery of AI features — able to take an agentic/AI feature from backend integration through to a usable front-end, not just a notebook prototype.
- Daily, hands-on use of Claude Code (or an equivalent agentic CLI) as a primary development tool — comfortable working through multi-step agentic sessions and reviewing and steering AI-generated diffs, rather than occasional autocomplete-style use.
- Prompt engineering — designing and iterating on system prompts as production software contracts, not one-off experiments.
- Python proficiency as the preferred language for AI/agent tooling; comfort with async patterns a plus.
- Evaluation and observability literacy — able to reason about whether an agent’s output is correct and instrument it to prove so.
Desirable:
- Claude Agent SDK experience — building custom agents, defining tools, and wiring agent loops.
- Working knowledge of agent primitives: hooks (deterministic pre/post-tool-call controls), skills (progressive-disclosure, load-on-demand instructions), subagents/multi-agent delegation, and session/state management.
- Experience authoring custom skills or slash commands for Claude Code to codify team-specific workflows.
- Exposure to MCP (Model Context Protocol) for connecting agents to internal tools and data sources.
- Working knowledge of RAG patterns and vector store integration (e.g. Qdrant, pgvector, Pinecone).
- Awareness of AI-specific risk areas relevant to a regulated environment (OWASP LLM Top 10, hallucination/determinism concerns, and auditability of agent decisions).
