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.

15 years full time education

📌 AI Infrastructure Architect (Pune)
🏢 Accenture
📍 Pune