AI Engineer
Job in
Palo Alto, Santa Clara County, California, 94306, USA
Listing for:
Elevait Solutions
Full Time
position
Listed on 2026-11-08
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Backend Developer, Cloud Engineer - Software
Job Description & How to Apply Below
Job Title: Applied AI Engineer
Industry: Technology
Location: Palo Alto, CA
Our client is a publicly traded data security software company headquartered in Silicon Valley, serving enterprises worldwide with backup, recovery, and cyber resilience solutions.
Top 3 Skills- Python development for LLM-powered applications and AI agents
- Agentic AI systems, including tool orchestration, MCP integrations, and automated LLM evaluations
- Cloud-native backend and API development (REST, GraphQL, OAuth2, RBAC)
- Assess where agentic approaches outperform conventional solutions for internal workflows
- Design and build agentic systems covering tool orchestration, agent reasoning, memory, MCP integrations, and human-in-the-loop steps
- Build automated evals, simulation tests, and regression frameworks to keep AI systems reliable as they scale
- Implement AI guardrails, data lineage, auditability, and responsible AI practices
- Prototype and evaluate emerging AI tools and technologies
- Deliver pilots, proofs of concept, and scalable implementations across engineering teams
- Integrate agents with enterprise APIs and SQL/No
SQL databases using role-based access controls - Partner with product, security, platform, and business teams to take AI use cases to production
- 4+ years of professional software engineering, including 1+ year building LLM-powered applications or agents
- Strong Python skills
- Hands‑on experience building agentic workflows with tool calling and a leading LLM SDK such as OpenAI or Anthropic
- Backend fundamentals, including REST or GraphQL APIs, authentication and authorization patterns (OAuth2, SAML, RBAC), and SQL/No
SQL databases - Working knowledge of a cloud platform (AWS or GCP), including compute, storage, and managed AI services
- Go (Golang) experience
- Production ownership of multi-agent systems at scale
- Agent frameworks such as Lang Graph, Google ADK, Mastra, or the Claude Agent SDK
- Evaluation and observability tooling such as Langfuse, Lang Smith, or Braintrust
- Building custom MCP servers
- Docker and Kubernetes
- Inference cost optimization for scaling agent deployments
- AI coding agents such as Claude Code, Git Hub Copilot, Cursor, or Windsurf
- RAG architectures, including vector databases, embedding models, chunking, and hybrid search
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