Software Engineer
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Role details
Tech stack
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Job description
You’ll sit between the customer and the product team: scoping the problem, writing production code in Python, and getting it live. Remote, US-based.
Responsibilities
Work with customer engineering and business teams to scope AI use cases and decide what’s worth building.
Build and deploy LLM applications: RAG pipelines, multi-step agents, and tool integrations over MCP.
Connect models to the customer’s systems: APIs, databases, data warehouses, SSO.
Requirements
8+ years in software engineering, with recent work shipping LLM-powered systems to production.
Required Skills
Strong Python, plus TypeScript or another backend language.
Hands-on work with LLM APIs from OpenAI, Anthropic (Claude), or Google (Gemini).
Experience with LangChain, LangGraph, LlamaIndex, Model Context Protocol (MCP), or the OpenAI Agents SDK.
Vector search with pgvector, Pinecone, or Weaviate.
Cloud deployment on AWS, Azure, or GCP, including Bedrock, Azure OpenAI Service, or Vertex AI.
You’re comfortable in front of a customer’s VP in the morning and in their codebase that afternoon.
Preferred Skills
Daily use of Claude Code or Cursor.
Agent-to-agent work using Google’s A2A protocol.
Prior consulting, solutions engineering, or customer-facing engineering roles.
Experience with HIPAA or PII-regulated data.
About the company
Forward deployed engineer, AI (remote)Our client puts engineers directly inside customer environments to build AI systems that work on messy, real data.
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