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.
About the role
- Senior Applied AI Engineer building production AI agents for Tango Analytics’ real estate technology platform. Designing retrieval, evaluation, safety, and human-review capabilities for customer workflows.
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, including chunking, hybrid retrieval, grounding, and citation to source page and paragraph
- Contribute agent evaluations using golden datasets, LLM-as-judge and deterministic scorers, and CI regression suites
- Diagnose quality failures and correct retrieval, prompt, tooling, model, or ground-truth issues
- 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
- Experience with testing, code review, CI/CD, and production ownership
- Production experience with an agent orchestration framework; LangGraph strongly preferred
- 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, 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 regarding hallucination, prompt injection, and silent degradation
- Preferred: graph-backed agent memory or knowledge graphs, such as Neo4j
- Preferred: production vector and hybrid retrieval stores, such as pgvector, Pinecone, Weaviate, or Qdrant
- Preferred: async task orchestration for long-running document pipelines, such as Celery/Redis or equivalent
- Preferred: 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 environment
- Inclusive and collaborative culture
- Equal opportunity employment
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