Description
We're looking for a Senior AI/ML Engineer to design and build the foundational AI layers, multi-step agentic workflows, and developer tooling for the broader engineering organization. You'll focus on the internal runtime for AI: implementing prompt frameworks, enforcing deterministic structured outputs, and deploying production-grade Human-in-the-Loop state automations — turning raw context into reliable, zero-hallucination agent-based actions.
Requirements
Must-Have Requirements
- Overall Experience: 7+ years in Backend Software Engineering and AI/ML Application Engineering
- Agentic Architecture: 2+ years engineering multi-step LLM workflows, autonomous agent loops, and multi-agent orchestration frameworks in production
- Developer Platform Enablement: experience building internal SDKs, tools, or structured pipeline abstractions used by other product engineering teams to ship AI features rapidly
- Proficiency in Multi-Step Agentic Workflows & Tooling
- Proficiency in Advanced Amazon Bedrock & Prompt Engineering
- Proficiency in Structured Output Pipelines & Performance Ingestion
- Proficiency in State Management, Automation Consistency & HITL
- Production fluency in Python
- Proficiency in TypeScript/Node.js for Vercel AI SDK and AWS edge workers
Preferred Experience
- Vercel AI SDK, LangGraph, or LlamaIndex for agentic orchestration
- Reliable tool-calling (function-calling) interfaces for LLM-driven internal system navigation
- Short-term and long-term agent memory architectures with ultra-low-latency in-memory stores (Amazon MemoryDB / Redis OSS / Valkey)
- Amazon Bedrock APIs (foundational model invocation and chaining for agent loops)
- Programmatic prompt optimization, few-shot prompting, dynamic context injection, and prompt caching
- Amazon Bedrock Guardrails (safety gating, prompt injection mitigation, PII redaction)
- Type-safe schema enforcement with Pydantic (Python) or Zod (TypeScript)
- Ingestion workers consuming Amazon MSK (Kafka), SQ