AI Engineer - Google ADK

Job Description:

Must-Have Technology Stack: Python | Cloud | Anthropic Claude | LangGraph OR LangChain | Google ADK | Generative AI / LLM | AI Agents

Job Summary

We are seeking an experienced AI Engineer to design, develop, and deploy AI-powered applications and agentic workflows using Python, Cloud technologies, Anthropic Claude, and LangGraph or LangChain. The ideal candidate will have hands-on experience building production-grade GenAI solutions, integrating LLMs with enterprise applications, and developing intelligent agents using modern AI frameworks.

Key Responsibilities

Design and develop LLM-powered applications and AI agents using Python.

Build agentic workflows using LangGraph or LangChain.

Develop solutions leveraging Anthropic Claude and other foundation models.

Work with Google ADK (Agent Development Kit) to build and orchestrate AI agents.

Integrate LLMs with enterprise APIs, databases, tools, and cloud services.

Develop RAG pipelines, prompt engineering solutions, tool/function calling, and multi-step agent workflows.

Deploy and operate AI applications in cloud environments.

Implement testing, monitoring, logging, security, and performance optimization for AI systems.

Collaborate with product, engineering, and business teams to translate requirements into scalable AI solutions.

Required Skills

Strong hands-on Python development experience.

Proven experience building Generative AI / LLM applications.

Strong experience with Anthropic Claude Must Have.

Hands-on experience with LangGraph OR LangChain Must Have.

Experience with Google ADK (Agent Development Kit) Must Have.

Strong understanding of Cloud platforms and cloud-native application development.

Experience with AI agents, RAG, prompt engineering, tool/function calling, and LLM orchestration.

Experience integrating AI solutions with REST APIs, databases, and enterprise systems.

Strong understanding of software engineering practices, APIs, CI/CD, and production deployments.

Preferred Qualifications

Experience with AWS, Google Cloud Platform, or Azure.

Experience with vector databases and embedding technologies.

Familiarity with LLM evaluation, observability, and AI safety/guardrails.

Experience developing scalable microservices using Python frameworks such as FastAPI.

Experience working in Agile development environments.