Description

Required Technical Skill Set:

•           Generative AI & LLMs (RAG, embeddings, prompt engineering)

•           Agentic AI & GenAI frameworks (LangChain, LlamaIndex, LangGraph)

•           Cloud AI platforms (Azure OpenAI, AWS Bedrock)

•  Cloud architecture (AWS / Azure)

•    MCP, API, microservices, and enterprise integrations

•    MLOps / LLMOps, security & Responsible AI

Desired Experience Range:

•  20+ years of overall IT experience

•   3+ years of hands‑on experience in AI / ML / Generative AI solutioning

•  Prior experience as Solution Architect / Cloud Architect / AI Architect

Desired Competencies (Technical/Behavioral Competency)

Strong understanding of LLMs and GenAI concepts (RAG, embeddings, vector databases, agents) Hands‑on experience with GenAI platforms such as:
AWS Bedrock & Azure OpenAI
Open‑source frameworks (LangChain, LlamaIndex, CrewAI, LangGraph, etc.) Cloud architecture expertise (AWS & Azure ) MCP, API, microservices, and integration architecture experience Data engineering and data platform knowledge (structured & unstructured data) Experience designing enterprise‑scale AI/ML or GenAI solutions Experience in agentic AI, workflow automation, or AI copilots Exposure to MLOps / LLMOps and model lifecycle management Strong understanding of non‑functional requirements: security, scalability, performance, cost Familiarity with Agile delivery models and DevSecOps practices Strong communication and presentation skills Ability to engage with senior stakeholders and customers Leadership and mentoring capabilities

Key Skills

Education

Any Gradute