Applied AI Developer / SME

SolutionIT, Inc.

San Ramon, CA, United States

15 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

2 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Microsoft Windows Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services User Authentication Cloud Computing Databases Data Security Database Queries Python (Programming Language) NoSQL OAuth

+12 more

Role-Based Access Control Security Assertion Markup Language (SAML) Software Engineering SQL Databases Systems Integration Google Cloud Large Language Models Multi-Agent Systems Backend AI Platforms Graphql Gsuite

Requirements

7+ years of professional software engineering, with at least 2 years focused on applied AI in production systems.
Proficient in Python and/or go; comfortable reading and writing in the other.
Proven experience building and scaling multi-agent or agent-driven systems in production - real-world operational ownership, not just simple LLM workflows.
Hands-on experience with Google Gemini Enterprise and the Agent Development Kit (ADK), or comparable enterprise agent platforms, including agent runtime, agent/tool registration, identity, and observability.
Hands-on experience with modern agent ecosystems, including frameworks (e.g., Google ADK, Lang Graph, Mastra, Claude Agent SDK), observability and evals tooling (e.g., Agent Observability, Lang fuse, Lang Smith, Braintrust), MCP implementations, and leading AI SDKs across a multi-model / BYOLLM environment (e.g., Gemini/Vertex AI, Anthropic (Claude), OpenAI, LLAMA).
Strong systems and backend architecture fundamentals - designing scalable, reliable systems and handling infrastructure, performance, failure modes, cost, and deployment concerns.
Good understanding of cloud-native environments, with Google Cloud (Google Cloud Platform) and Vertex AI strongly preferred (and/or AWS) - compute, storage, networking, and managed AI services.
Experience designing and integrating with enterprise APIs (REST, GraphQL) including authentication and authorization patterns (OAuth2, SAML, API keys, RBAC) and connecting agents to enterprise data sources across Google Workspace and Microsoft 365. Comfortable working with backend databases (SQL and NoSQL) - writing queries, understanding data models, and building data access layers that enforce role-based access control aligned with Agent Identity and Agent Security.