Java API Integration Engineer

• Backend/Systems Experience 3+ years building production backend or distributed systems (pre-AI experience required)
• Production AI Systems Has shipped AI/LLM features serving real users at scale not just prototypes or demos
• Agentic Systems Has built AI agents, skills, tools, or MCP (Model Context Protocol) integrations
• Python Proficient for backend development
• Secondary Language Working knowledge of Go, TypeScript, or Rust
• Cloud Infrastructure Deep experience with AWS/Google Cloud Platform/Azure cost optimization, compute decisions, not just deployment
• Container & Orchestration Hands-on with Docker and Kubernetes can build, deploy, debug, and scale services themselves
• LLM Integration Understands token economics, context limits, rate limiting, structured outputs, API failure modes
• LLM Evaluation Understands how to evaluate LLM outputs and the inherent challenges (non-determinism, quality measurement, regression detection)
• Hands-On Engineer Not just an architect writes code, debugs production issues, deploys their own work

Preferred / Differentiators

• Built multi-step agentic workflows with tool use and function calling
• Experience with agent orchestration frameworks (LangGraph, CrewAI, or custom)
• Built guardrails, fallbacks, or graceful degradation for AI systems
• Streaming inference and async agent orchestration, * AI experience is mainly academic, research, or tutorial-based
• No production systems experience (only notebooks/demos)
• Looking for entry-level role with heavy mentorship
• Background is primarily data science/analytics rather than engineering
• “Architects” who don’t write or deploy code themselves