AI Engineer building generative and agentic AI solutions for Trillium Health Partners’ hospital workflows. Connecting intelligent agents to clinical systems and scaling responsible healthcare automation.
About the role
- Senior Applied AI Engineer building production AI agents for Tango Analytics’ real estate technology platform. Designing retrieval, evaluation, safety, and human-in-the-loop capabilities.
Responsibilities
- Build and ship Tango’s first AI-powered product
- Design, build, and ship production AI agents on LangGraph
- Own agents end to end, including graph design, tool definitions, prompt and context engineering, durable execution, failure and retry behavior, and cost and latency budgets
- Build agent tooling against internal systems over MCP, using direct API calls and agent-to-agent interfaces where appropriate
- Deliver human-in-the-loop review flows with interrupt points, confidence surfacing, and correction paths
- Build and tune retrieval covering chunking, hybrid retrieval, grounding, and citations back to source page and paragraph
- Contribute golden datasets, LLM-as-judge and deterministic scorers, and CI regression suites
- Diagnose quality failures and correct the appropriate layer
- Own agent-level safety behavior, including prompt-injection resistance, PII handling, refusal, and escalation paths
- Partner with Product to translate accuracy thresholds, confidence disclosure, and human-in-the-loop triggers into shipped behavior
- Work with Platform Engineering on deployment and Data Platform on curated datasets
- Feed agent session and usage analytics into the warehouse
- Transition reference agents to domain teams and contribute to the shared agent quality standard
Requirements
- 7+ years of professional software engineering experience
- 2+ years building LLM-powered systems that reached production and real users
- Strong expertise with Python and its service stack, including FastAPI, Pydantic, or equivalents
- Engineering discipline in testing, code review, CI/CD, and production ownership
- Production experience with an agent orchestration framework
- Hands-on depth with at least one frontier model API
- Hands-on experience with LLM evaluation, including golden datasets, LLM-as-judge, deterministic scorers, regression testing, and release gating
- Experience with MCP tool servers or comparable tool and function-calling protocols
- Experience with multi-agent patterns
- Production RAG and retrieval experience, including chunking strategy, hybrid retrieval, grounding, citation, and diagnosing retrieval failures
- Experience with LLM observability and tracing, such as LangSmith, Langfuse, Arize, or equivalent
- Experience with prompt and version management
- Sound judgment about hallucination, prompt injection, silent degradation, and acceptable versus unacceptable failures
- LangGraph strongly preferred; LangChain, OpenAI or Claude Agents SDKs, or equivalent frameworks considered
- Preferred experience with graph-backed agent memory or knowledge graphs
- Preferred experience with production vector and hybrid retrieval stores
- Preferred experience with async task orchestration for long-running document pipelines
- Preferred experience with document intelligence and information extraction at scale, including OCR, layout-aware parsing, and structured extraction from long documents
- Applicants must be authorized to work in the U.S. for any employer
- Tango cannot sponsor employment-based visas at this time
Benefits
- Health, dental, and vision insurance
- 401(k) plan with company match
- Generous paid time off
- Fully remote work arrangement
- Inclusive and collaborative culture
- Competitive compensation
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