Requirements* Defines end-to-end AI solution architectures across cloud, data, models, and integration layers, emphasizing scalability, security, and compliance. Guides technology selection and reference implementations We are seeking a highly experienced, hands-on Senior AI Agent Engineer to lead the design, development, and deployment of a scalable Agentic AI platform focused on knowledge-driven reasoning and enterprise transformation The ideal candidate will have a proven track record in cloud modernization and migration, hands-on expertise in Agentic AI design and deployment,
and the ability to transform enterprise services into AI-driven, searchable APIs through Knowledge Record Management and build the Reasoning/orchestration layer This role will drive the creation of an Agentic AI framework that integrates deterministic and probabilistic knowledge systems using Vector Databases and Graph Databases, enabling dynamic reasoning, orchestration, and intelligent automation across enterprise operations.
Key
Responsibilities* Design and develop a modular Agentic AI architecture supporting dynamic agents, tools, and reusable skills. • Build reasoning and orchestration layers leveraging Deterministic logic (rules, workflows, enterprise patterns) and Probabilistic AI (LLMs, embeddings, semantic reasoning) • Implement agent orchestration using frameworks such as(Model Context Protocol (MCP / FastMCP), Google ADK, LangGraph, LangChain, RAG • Build reusable agent patterns, orchestration layers, and capability abstractions • Architect enterprise-grade Knowledge Record Management systems(Vector DBs for semantic retrieval and Graph DBs for relationship-driven reasoning • Enable hybrid retrieval architectures (RAG + Graph-based reasoning). • Build AI-searchable APIs by transforming enterprise services into structured knowledge layers.• Implement context-aware memory systems for agents (short-term, long-term). • Design, build, and deploy production-grade AI solutions and agents (not just PoCs). • Integrate LLMs (Vertex AI, OpenAI, Claude Code etc.) for reasoning, summarization, and decision-making. • Develop multi-agent systems, Tool-use / function-calling workflows and AI-powered APIs and microservices • Build UI/interaction layers where needed (ReactJS, Flask-based interfaces). • Implement tool use, function calling, and multi-agent collaboration. • Analyze legacy systems and business processes and translate them into AI-driven solutions. • Define and implement AI-specific SDLC frameworks: • Design → Build → Evaluate → Deploy → Monitor → Improve
* Leverage and establish enterprise AI patterns and standards: Prompt engineering and Agent design patterns • Ensure consistency, quality, and scalability across implementations. • Establish end-to-end lifecycle management for AI agents. Automated evaluation pipelines (accuracy, hallucination, drift) • Implement monitoring, observability, and guardrails: Safety, compliance, explainability. • Design and deploy scalable AI solutions on: Google Cloud Platform (Google Cloud Platform) (preferred)/Azure
Section IV - Job Qualifications & Skills
Section Details / Example Content
Domain
Soft Skills - Excellent communication - Team collaboration - Documentation and knowledge sharing
Education
Requirements Bachelor''''s Degree in Computer Science, Information Technology or related field
Required
Qualification
Experience • 10+ years in Solution/Enterprise Architecture/ Software Engineering • 5+ years’ experience as a Lead/Senior architect or senior technical lead for large IT projects spanning multiple enterprise systems • 2+ years of hands-on AI development and deployment • Proven experience delivering production-grade AI products • Strong track record in cloud modernization and migration initiative • Key knowledge of all Software Development Life Cycle (SDLC) activities, including ideation, design, implementation, validation of functional and non-functional aspects, and Day 2 operations.
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