AI Engineer
- Micasa Global
2 Days Ago
NA
C2C
Dallas-TX
13-15 Years
Required Skills: Google ADK, LangGraph, AutoGen, CrewAI, ramp on ADK, Python Development, Gemini, Claude, OpenAI,, REST APIs, backend service integration, Vertex AI, Cloud Run, IAM, Secrets Manager, Model Context protocol, SQL, Snowflake Cortex, Cortex Analyst, Salesforce Data models, Rest.js, Next.js, Node.js, Nest.js
Job Description
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
- 12+ 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 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
- 12+ 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
