What are the responsibilities and job description for the Agentic AI Architect position at Virtusa?
JD - Agentic AI Architect
Seeking for an Agentic AI Architect to design, build, and deliver production‑grade agentic AI systems using MCP (Model Context Protocol) and Google Agent Development Kit (ADK). This role requires strong expertise in AI/ML architecture, Python development, and cloud-native platforms, with a proven track record of taking AI solutions from prototype to enterprise production.
Key Responsibilities
Strong hands-on experience with Agentic AI systems, MCP, and Google ADK.
Demonstrated success delivering AI/ML solutions to production.
Deep expertise in AIML architecture and advanced Python development.
Experience with GCP preferred; AWS/Azure experience is a plus.
Proven leadership, research capability, and stakeholder communication skills.
Seeking for an Agentic AI Architect to design, build, and deliver production‑grade agentic AI systems using MCP (Model Context Protocol) and Google Agent Development Kit (ADK). This role requires strong expertise in AI/ML architecture, Python development, and cloud-native platforms, with a proven track record of taking AI solutions from prototype to enterprise production.
Key Responsibilities
- Architect and implement agent-based AI solutions, including multi-agent workflows, tool integration, memory, and orchestration using MCP and Google ADK.
- Lead end-to-end delivery of agentic solutions, ensuring reliability, scalability, observability, and cost efficiency in production.
- Design robust AI/ML architectures for LLM-based systems, including prompt strategies, RAG, and evaluation frameworks.
- Write and review production-quality Python code and establish testing, CI/CD, and deployment best practices.
- Build and deploy solutions primarily on GCP (Vertex AI, Cloud Run, GKE), with transferable knowledge across AWS and/or Azure.
- Research emerging agentic AI patterns and translate innovations into practical, business-ready solutions.
- Provide technical leadership, mentor engineers, and collaborate closely with business, product, platform, and IT stakeholders.
Strong hands-on experience with Agentic AI systems, MCP, and Google ADK.
Demonstrated success delivering AI/ML solutions to production.
Deep expertise in AIML architecture and advanced Python development.
Experience with GCP preferred; AWS/Azure experience is a plus.
Proven leadership, research capability, and stakeholder communication skills.