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Applied AI Senior Engineer
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Recutify Inc.
Sunnyvale, CA (In Person)
$119,600 Salary, Full-Time
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Job Description
Applied AI Senior Engineer Recutify Inc. Sunnyvale, CA Job Details $55
- $60 an hour 18 hours ago Qualifications AI models Containerization systems Systems integration Software engineering Public Cloud Scalable systems IT infrastructure Reducing cloud infrastructure costs Quality performance measurement Machine intelligence Model deployment APIs Developing and maintaining backend systems System deployment Model evaluation Production troubleshooting
Full Job Description Title:
Applied AI Senior Engineer Location:
Austin, TX/Sunnyvale, CA (Onsite)Relocation Works Duration:
12+ Months Video Interviews 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