Design, develop and evolve agents and workflows using MCP-based architectures
Build RAG pipelines and context-retrieval mechanisms using vector databases
Integrate agents with APIs, tools and external services to execute complex flows
Develop agents in Python using Google ADK
Build and maintain agentic flows with LangChain and LangGraph
Integrate AI models and services via Vertex AI and Gemini models
Implement build, test and deployment pipelines for agents and workflows
Define architectural standards, reusable components and technical governance guidelines for the platform
Ensure solution observability through logs, metrics and tracing
Collaborate with technical teams to ensure consistent integration between AI agents and enterprise applications
Design solutions aligned with business processes, integrations and objectives
Ensure developed components are scalable, reusable and prepared for continuous evolution

Strong experience in Python development
Hands-on experience building agents, intelligent workflows and integrations with generative AI models
Experience with LangChain and LangGraph
Knowledge of MCP-based architectures
Experience with RAG pipelines and vector databases
Experience integrating APIs, tools and external services
Experience with Vertex AI and Gemini models
Knowledge of application build, test and deployment practices
Ability to define technical standards, reusable abstractions and engineering best practices
Experience with observability, including logs, metrics and tracing
Ability to collaborate with engineering, architecture teams and technical squads
Systemic thinking to understand data flows, integrations and constraints of enterprise environments

Senior AI Engineer

Key skills