Job Summary

We are looking for GenAI / Agentic AI Architects in senior levels to lead the conceptualization, architect, build, and deploy processes of AI applications leveraging LLMs and agentic frameworks. You will participate in customer discussion in identifying use cases and lead the end-to-end SDLC—from conceptualization to production rollout —and collaborate closely with stakeholders to deliver robust, scalable AI solutions. You will lead the end-to-end technical ownership by interacting with customers and development teams.

Key Responsibilities

• Participate in customer meetings, workshops in understanding the business problems and conceptualizing the solution and implementation strategy.
• Architect the scalable solutions aligned to the preferred technology stack, tooling, interfaces and integrations of GenAI and Agentic AI applications.
• Lead the design and development of AI solutions using frameworks such as Microsoft Agent Framework – Autogen, Semantic Kernel, Copilot Studio andGen AI tooling like MCP servers.
• Guide / mentor in selecting and implementing the relevant data science / machine learning algorithms and AI led automation to the developers.
• Collaborate with customers/stakeholders on project status and deliverables.

Skill Requirements

• GenAI / Agent frameworks:  Azure AI Foundry, Azure OpenAI, Autogen or LangChain, LangGraph.
• Python (scripting, data manipulation); familiarity with Python packages like NumPy, Pandas, Matplotlib, Scikit Learn etc.
• Knowledge of windows system architecture, device drivers / firmware, windows devices, product life cycle management knowledge is desired.
• Understanding of machine learning fundamentals: supervised vs. unsupervised learning, neural networks, NLP.
• Experience with RAG pipelines, vector databases, prompt optimization, and safety/guardrails.
• Strong knowledge of Azure platform and PaaS services. Familiarity with Power Platform and  Copilot Studio is plus.

Other Requirements

• Communication leveraging the Hugging Face models, ML frameworks like PyTorch / Tensorflow, and diffusion models (for image generation).
• Design experience of GenAI tools: MCP Server, Agent 2 Agent protocols
• Exposure to MLOps (model versioning, deployment, monitoring).
• Cloud certifications  (Microsoft Azure) is a plus.
• Production-ready GenAI/Agentic applications.
• Fine-tuned models and reproducible experiments.
• Clear documentation, test coverage, and deployment pipelines.
• Regular updates on project status and deliverables to stakeholders.
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