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 : AI Agents & Workflow Integration Good to have skills : NA Minimum 7.5 Year(s) Of Experience Is Required Educational Qualification : 15 years full time education Summary: The Agentic Manager is responsible for end-to-end design, development, and operationalization of Agentic AI solutions for Infrastructure Managed Services. This role requires deep hands-on expertise across agentic frameworks, automation, AI integration, and infrastructure domains (Data Center, Cloud, Network, Compute, Storage etc). Collaboration with various teams to align infrastructure capabilities with project goals is a key aspect of daily activities.

Roles & Responsibilities: Agentic AI Engineering (Primary Accountability)

Design and implement agentic AI solutions addressing infrastructure operations use cases

Build single-agent and multi-agent systems using planner–executor, tool-using, and reflection patterns.

Develop reusable agent frameworks, tools, and workflows aligned with enterprise standards.

Infrastructure Domain Ownership

Posses strong Infrastructure Managed Services expertise

Act as a technical domain specialist for infra-focused agentic solutions.

Platform & Tool Integration

Integrate agents with enterprise platforms including:

ITSM tools (ServiceNow – Incident, Change, CMDB)





Monitoring & observability tools (SCOM, Dynatrace, AppDynamics, Prometheus, Grafana)

Automation platforms (Rundeck, Ansible, Terraform)

Develop secure Python-based tools and APIs that agents can reliably invoke.

LLM & Agent Framework Implementation

Work hands-on with LLMs in a model-provider-agnostic manner.

Implement agent capabilities using frameworks such as LangChain / LangGraph, AutoGen / CrewAI (or similar)

Manage Memory and context optimization, and cost, latency, and reliability trade-offs

Security, Governance & Reliability

Ensure agent solutions comply with Enterprise security standards

Implement Human-in-the-loop controls, Guardrails and Failure handling and rollback mechanisms

Delivery & Stakeholder Collaboration

Independently own delivery of assigned agentic use cases.

Collaborate with Infrastructure SMEs, Platform and automation teams, and Architecture and governance teams

Produce clear technical documentation.

Professional & Technical Skills: Must Have Skills: Proficiency in AI Agents & Workflow Integration.

Python (advanced) – automation, APIs, async workflows

REST APIs, authentication mechanisms, JSON

Solid knowledge of Data Center and Cloud administration, as well as Monitoring, Observability and ITSM platforms.

Experience building agent-based systems (beyond chatbots)

Strong understanding of Context and memory management

Experience with AIOps or auto-remediation platforms

Exposure to MCP Additional Information: The candidate should have minimum 7.5 years of experience in AI Agents & Workflow Integration.

This position is based at our Pune/Bengaluru office.

A 15 years full time education is required.

📌 AI Infrastructure Architect (Pune)
🏢 Accenture in India
📍 Pune