AI Infrastructure Architect

Project Role : AI Infrastructure Architect

Project Role Description : Architect and build custom Artificial Intelligence (AI) infrastructure/hardware solutions. Optimize AI infrastructure/hardware performance, power consumption, cost and scalability of computational stack. Advise on AI infrastructure technology and vendor evaluation, selection and full stack integration.

Must have skills : Microsoft Azure OpenAI Service

Good to have skills : NA

Minimum 7.5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary:

We are seeking a highly skilled Senior Agentic AI Developer to design, architect, and deliver next-generation intelligent agent solutions powered by Large Language Models (LLMs). The ideal candidate will bring deep hands-on expertise in building agentic AI systems using LangChain and LangGraph, and deploying scalable, enterprise-grade solutions leveraging Azure OpenAI (GPT-5.0 and above). This role focuses on developing autonomous, reasoning-driven AI agents capable of solving complex business problems, orchestrating workflows, and driving intelligent automation at scale.

Key Roles and Responsibilities:

• Solution Architecture & Design
  
  

Architect end-to-end Agentic AI solutions using modern frameworks such as LangChain and LangGraph.

Design multi-agent systems with capabilities like reasoning, planning, memory, and tool orchestration.

Define scalable architectures for distributed agents aligned with enterprise needs and cloud best practices.

Translate business problems into AI-driven workflows and agent-based solutions.

• Development & Implementation
  
  

Build and deploy intelligent agents using Azure OpenAI services and advanced GPT models.

Develop stateful, multi-step agent workflows leveraging LangGraph constructs such as nodes, edges, and shared state.

Implement RAG (Retrieval-Augmented Generation), tool integrations, and external API orchestration.

Create reusable agent components, prompt templates, and orchestration pipelines.

• LLM & Agent Optimization
  
  

Fine-tune prompts, workflows, and agent decision-making loops (ReAct, planning agents, etc.).

Optimize performance, latency, cost, and response quality of LLM-based systems.

Implement memory management (short-term, long-term, vector-based).

• Enterprise Integration & Deployment
  
  

Integrate agents into enterprise ecosystems (APIs, databases, enterprise apps).

Deploy solutions on Azure cloud, ensuring scalability, security, and reliability.

Work with DevOps teams for CI/CD pipelines, monitoring, and observability.

• Governance, Security & Responsible AI
  
  

Ensure compliance with Responsible AI, data privacy, and security standards.

Implement guardrails, validation layers, and safe AI practices.

Participate in design reviews and risk assessments.

• Collaboration & Leadership
  
  

Collaborate with cross-functional teams (Product, QA, DevOps, Business).

Mentor junior developers and contribute to best practices and reusable frameworks.

Drive innovation through POCs, accelerators, and reusable assets.

Required Skills & Experience:

Core Technical Skills

Strong hands-on experience with:

• LangChain & LangGraph for agent orchestration
• Azure OpenAI (GPT-5.0 or higher) and LLM-based application development
  
  

Deep understanding of:

• Agentic AI concepts: reasoning, planning, autonomy, tool usage
• Multi-agent systems and orchestration
  
  

Proficiency in:

• Python (must-have)
• API development (FastAPI/REST)
• Data integration and pipelines
  
  

AI/ML & LLM Expertise

Experience with:

• Prompt engineering and few-shot learning
• RAG pipelines, embeddings, and vector databases
• Knowledge graphs and contextual AI systems
  
  

Understanding of LLM evaluation, tuning, and monitoring.

Cloud & DevOps

Hands-on experience with:

• Azure AI services, Azure OpenAI, AI Foundry
• CI/CD pipelines, containerization (Docker/Kubernetes preferred)
• Monitoring tools (App Insights, Log Analytics)
  
  

Additional Information:

• The candidate should have minimum 7.5 years of experience in Microsoft Azure OpenAI Service.
• This position is based at multiple locations.
• A 15 years full time education is required.