AI MCP Architect/ Integration Arch - Agentic AI, MCP, OAuth2, SAML, Op

SN Required Information

Details

Automation Solution Architect

2 Required Technical Skill Set

• Experienced

  AI Solution Architect

  to lead the design and implementation of cutting-edge AI solutions, with a strong focus on

  Generative AI

  ,

  Agentic AI systems

  , and

  Cloud-native architectures

  .
• Good understanding of MCP
• Strong understanding of AI/ML concepts; exposure to GenAI tools (e.g., ChatGPT, Copilot, Claude, etc.)

Desired Competencies (Technical/Behavioral Competency)

Must-Have

• 5+ years of experience in AI/ML solution design, with at least 2 years in Generative AI and Agentic AI.
• Deep understanding of LLMs (e.g., GPT, Claude, LLaMA), prompt engineering, and fine-tuning techniques.
• Experience with Agentic AI frameworks (e.g., LangChain, AutoGen, CrewAI, or similar).
• Strong background in cloud architecture and services (e.g., SageMaker, Vertex AI, Azure ML).
• Proficiency in Python, APIs, containerization (Docker), and orchestration (Kubernetes).
• Good Communication skills and stakeholder management skills

Good-to-Have

• Certifications in cloud platforms (AWS/Azure/GCP).
• Experience with vector databases (e.g., Pinecone, FAISS, Weaviate).
• Familiarity with MLOps tools (e.g., MLflow, Kubeflow).
• Contributions to open-source AI projects or publications in AI/ML.

SN

Role descriptions / Expectations from the Role

1

Generative AI models (LLMs, diffusion models, etc.)

2

Collaborate with cross-functional teams to define AI strategies, use cases, and implementation roadmaps.

3

cloud platforms

4

Evaluate and integrate open-source and commercial AI tools, APIs, and frameworks.

5

Lead technical discussions, proof-of-concepts, and solution demos with stakeholders and clients.

6

Ensure compliance with data governance, security, and ethical AI practices.

7

Quickly adoption of the new technology and conducting the POC

8

Guiding the team on the technical and operational issues