Company:A Large Global Organization

Key Skills: Agentic AI, AWS, LLM, Lang chain, Azure, Lang graph, GenAI Architect, DevOps, CICD, Containerization (Docker, Kubernetes)

Roles and Responsibilities:

- Lead the architecture and development of production-grade Generative AI, Agentic AI, RAG, and intelligent automation solutions.
- Evaluate business and technical requirements to select appropriate Azure, AWS, no-code, low-code, or pro-code implementation approaches.
- Design scalable, secure, maintainable AI architectures and establish reusable engineering patterns for enterprise adoption.
- Lead technical design reviews, technology evaluations, solution governance, and architecture decisions across distributed engineering teams.
- Guide AI solutions through discovery, development, evaluation, deployment, monitoring, and continuous improvement while mentoring engineers.

Skills Required:

- 7 - 14 years of software engineering experience,



including significant experience architecting and leading production AI or intelligent automation solutions.
- Hands-on experience with Microsoft Azure and AWS for enterprise application and AI solution delivery.
- Strong experience designing Agentic AI and LLM-based applications, including AI orchestration and tool-calling workflows.
- Proficiency with LangChain and LangGraph for building AI workflows, agents, and production-grade orchestration solutions.
- Experience defining Generative AI architecture, including RAG, evaluation, guardrails, observability, security, and responsible AI controls.

Positive to Have:
- DevOps and CI/CD experience.
- Containerization experience with Docker and Kubernetes.

Education: Bachelor's or master's degree in Computer Science, Information Technology, Engineering, or a related discipline.

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