AI Engineer - Level 3
•30 days ago
| Estimated Pay info | Based on similar jobs in your market$18 per hour |
|---|---|
| Hours | Full-time, Part-time |
| Location | Richardson, Texas |
About this job
AI Engineer (Agent Development Kit / ADK)
Location: TX-Richardson / hybrid onsite
Duration: Till feb 2027, possible extension/conversion
About the Role
We're looking for an AI Engineer to design and build production-grade AI agents using Google's Agent Development Kit (ADK). You'll work on multi-agent systems that integrate with enterprise data platforms and business tools, taking agents from prototype through to reliable production deployment.
What You'll Work On
- Designing and building AI agents and multi-agent workflows using ADK
- Agent orchestration patterns: tool use, function calling, sub-agent delegation, and state/session management
- Integrating agents with enterprise data sources (Snowflake, Salesforce, or similar) and internal APIs
- Deploying and scaling agents on Google Cloud (Vertex AI Agent Engine or equivalent)
- Evaluating and tuning agent performance, latency, and cost across different model backends
- Building tooling and guardrails around agent behavior: observability, testing, and safety checks
- Collaborating with data engineering and platform teams to expose reliable, well-governed data to agents
Must Have
- Hands-on experience building agents with Google ADK (or comparable agent frameworks such as LangGraph, AutoGen, CrewAI, with strong ability to ramp on ADK)
- Strong Python development skills
- Experience with LLM APIs (Gemini, Claude, OpenAI, or similar) and prompt/tool design
- Understanding of agent architecture patterns: planning, tool orchestration, memory/state, multi-agent coordination
- Experience with REST APIs and backend service integration
- Familiarity with Google Cloud Platform (Vertex AI, Cloud Run, IAM, Secrets Manager)
Good to Have
- Experience with Model Context Protocol (MCP) or other agent-to-tool integration standards
- SQL proficiency, ideally with Snowflake (CTEs, Dynamic Tables, Views)
- Experience with Snowflake Cortex / Cortex Analyst
- Familiarity with Salesforce data models (Account IDs, object relationships)
- Experience with evaluation frameworks for LLM/agent output quality
- Background integrating agents into existing enterprise applications (React/Next.js, Node.js/NestJS)
Requirements
- 8+ years of software engineering experience, with recent focus on applied AI/agent systems
- Strong Python skills; TypeScript/JavaScript a plus
- Experience shipping AI features to production, not just prototypes
- Comfortable working independently in ambiguous, fast-evolving technical territory
- Clear communicator, able to explain agent behavior and architecture to both technical and non-technical stakeholders
What Success Looks Like
- Agents that are reliable, observable, and behave predictably in production
- Clean integration between agents and underlying enterprise data/systems
- Reduced manual effort for end users through well-scoped agent automation
Location: TX-Richardson / hybrid onsite
Duration: Till feb 2027, possible extension/conversion
About the Role
We're looking for an AI Engineer to design and build production-grade AI agents using Google's Agent Development Kit (ADK). You'll work on multi-agent systems that integrate with enterprise data platforms and business tools, taking agents from prototype through to reliable production deployment.
What You'll Work On
- Designing and building AI agents and multi-agent workflows using ADK
- Agent orchestration patterns: tool use, function calling, sub-agent delegation, and state/session management
- Integrating agents with enterprise data sources (Snowflake, Salesforce, or similar) and internal APIs
- Deploying and scaling agents on Google Cloud (Vertex AI Agent Engine or equivalent)
- Evaluating and tuning agent performance, latency, and cost across different model backends
- Building tooling and guardrails around agent behavior: observability, testing, and safety checks
- Collaborating with data engineering and platform teams to expose reliable, well-governed data to agents
Must Have
- Hands-on experience building agents with Google ADK (or comparable agent frameworks such as LangGraph, AutoGen, CrewAI, with strong ability to ramp on ADK)
- Strong Python development skills
- Experience with LLM APIs (Gemini, Claude, OpenAI, or similar) and prompt/tool design
- Understanding of agent architecture patterns: planning, tool orchestration, memory/state, multi-agent coordination
- Experience with REST APIs and backend service integration
- Familiarity with Google Cloud Platform (Vertex AI, Cloud Run, IAM, Secrets Manager)
Good to Have
- Experience with Model Context Protocol (MCP) or other agent-to-tool integration standards
- SQL proficiency, ideally with Snowflake (CTEs, Dynamic Tables, Views)
- Experience with Snowflake Cortex / Cortex Analyst
- Familiarity with Salesforce data models (Account IDs, object relationships)
- Experience with evaluation frameworks for LLM/agent output quality
- Background integrating agents into existing enterprise applications (React/Next.js, Node.js/NestJS)
Requirements
- 8+ years of software engineering experience, with recent focus on applied AI/agent systems
- Strong Python skills; TypeScript/JavaScript a plus
- Experience shipping AI features to production, not just prototypes
- Comfortable working independently in ambiguous, fast-evolving technical territory
- Clear communicator, able to explain agent behavior and architecture to both technical and non-technical stakeholders
What Success Looks Like
- Agents that are reliable, observable, and behave predictably in production
- Clean integration between agents and underlying enterprise data/systems
- Reduced manual effort for end users through well-scoped agent automation
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