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 contemporary 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 safe 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: 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)

- 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. Qualification 15 years full time education"

📌 AI Infrastructure Architect (Bengaluru)
🏢 Accenture
📍 Bengaluru