Applied AI

Role- Applied AI Senior Engineer


Type- Full Time


Location- Sunnyvale, CA/Austin, TX

Job Description:

Must-Have Requirements:


Requirement Details


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/GCP/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, Claude Agent SDK, Google ADK, OpenAI ADK)
• Built guardrails, fallbacks, or graceful degradation for AI systems
• Streaming inference and async agent orchestration
• Cost/latency optimization: caching, batching, prompt compression
• ML observability tools: Langfuse, Arize, Braintrust, W&B
• Retrieval systems (vector search, hybrid search) - as a tool, not the focus