Description

Requirements:

Experience: 8+ years of software engineering experience with 3+ years in a technical leadership capacity building multi-agent AI systems, FinOps tools, or LLM-powered platforms

Frameworks & Languages: Advanced proficiency in Python 3.11+, FastMCP, FastAPI, and Pydantic. Prior experience with object-oriented enterprise languages (e.g., Java) for seamless integration with core platform services and backend APIs

AI/LLM Architecture: Hands-on experience with Google ADK, Vertex AI, LiteLLM Gateway, Model Armor guardrails, prompt engineering, structured tool output parsing, and agent execution boundaries

Data & Cloud Platforms: Deep familiarity with the GCP ecosystem (BigQuery, GKE, Workload Identity), SQL schema design (FOCUS standard preferred), and partitioned/clustered OLAP architectures

Security & Governance: Experience implementing Zero Trust authentication (OAuth/KSA-to-GSA), RBAC, immutable audit logging, and API/MCP error specifications (RFC 7807/9457)

DevOps & Infrastructure: Proficiency with Docker builds, GKE deployment patterns, OpenTofu/Terraform, and CI/CD pipelines

Leadership Skills: Proven ability to coach, mentor, and influence teams beyond just writing and implementing solutions

Nice to have:

Experience with LangGraph / LangChain

Hands-on experience with Vertex AI

Working knowledge of modern DevOps and CI/CD practices

Familiarity with GCP infrastructure resources and their constraints, with the ability to identify optimal resources for designed AI agentic solutions

Key Skills

Education

Bachelor's degree