AI Engineer

Elevait Solutions LLC; Palo Alto (CA); In loco; USD 180.000 - 240.000; Tempo pieno

Descrizione del lavoro

A Silicon Valley-based, publicly traded data security software company is seeking engineers to design and build agentic AI systems, tools, and automated evaluation frameworks. You will work on memory, tool orchestration, and enterprise API integrations, partnering across product, security and platform teams to productionize AI use cases.

Ideal candidates have 4+ years in software engineering, hands-on experience with LLM-powered workflows, and strong backend/API knowledge.

Competenze

• 4+ years of professional software engineering including 1+ year building LLM-powered apps or agents.
• Hands-on experience building agentic workflows with tool calling and an LLM SDK such as OpenAI or Anthropic.
• Backend fundamentals with REST/GraphQL APIs, OAuth2/SAML/RBAC, and SQL/NoSQL databases.
• Experience with a cloud platform (AWS or GCP) including compute, storage and managed AI services.

Mansioni

• 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/NoSQL databases using RBAC.
• Partner with product, security, platform, and business teams to productionize AI use cases.

Conoscenze

Python development for LLM-powered

Agentic AI systems

Cloud-native backend & API development

Strumenti

Docker

Kubernetes

OpenAI API

Anthropic API

LangGraph

Descrizione del lavoro

Client Overview

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)

What You ll Do

• 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/NoSQL databases using role-based access controls
• Partner with product, security, platform, and business teams to take AI use cases to production

What We Need From You

• 4+ years of professional software engineering, including 1+ year building LLM-powered applications or agents
• 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/NoSQL databases
• Working knowledge of a cloud platform (AWS or GCP), including compute, storage, and managed AI services

Preferred / Bonus

• Go (Golang) experience
• Production ownership of multi-agent systems at scale
• Agent frameworks such as LangGraph, Google ADK, Mastra, or the Claude Agent SDK
• Evaluation and observability tooling such as Langfuse, LangSmith, or Braintrust
• Building custom MCP servers
• Docker and Kubernetes
• Inference cost optimization for scaling agent deployments
• AI coding agents such as Claude Code, GitHub Copilot, Cursor, or Windsurf
• RAG architectures, including vector databases, embedding models, chunking, and hybrid search