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:

1. 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.

2. 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.

3. 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).

4. 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.

5. Governance, Security & Responsible AI
Ensure compliance with Responsible AI, data privacy, and security standards.
Implement guardrails, validation layers, and secure AI practices.




Participate in design reviews and risk assessments.

6. 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:
o LangChain & LangGraph for agent orchestration
o Azure OpenAI (GPT-5.0 or higher) and LLM-based application development
Deep understanding of:
o Agentic AI concepts: reasoning, planning, autonomy, tool usage
o Multi-agent systems and orchestration
Proficiency in:
o Python (must-have)
o API development (FastAPI/REST)
o Data integration and pipelines

AI/ML & LLM Expertise
Experience with:
o Prompt engineering and few-shot learning
o RAG pipelines, embeddings, and vector databases
o Knowledge graphs and contextual AI systems
Understanding of LLM evaluation, tuning, and monitoring.

Cloud & DevOps
Hands-on experience with:
o Azure AI services, Azure OpenAI, AI Foundry
o CI/CD pipelines, containerization (Docker/Kubernetes preferred)
o 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.

15 years full time education

📌 AI Infrastructure Architect (India)
🏢 Accenture
📍 India