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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - AI Accelerated Development - **Company:** Signant Health - **Location:** Blue Bell, PA, United States (Remote available) - **Experience:** Starter - **Salary:** $150,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** .NET Framework, Artificial Intelligence, User Authentication, Microsoft Azure, C Sharp (Programming Language), Programming Tools, Python (Programming Language), Open Web Application Security, Data Streaming, Web Application Frameworks, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Backend, Build Management - **Published:** September 30, 2026 - **Apply:** https://www.careerjet.com/job/us38fab773fc1aca346bbb49a6f205aec6/eaa ## About the Role * 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). ## 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.