Salary
≈ $19k – $49k per year (Estimated)
Location
Hybrid (Pune, India)
Seniority
Architect
Confirmed on the employer's own hiring board on Oct 23, 2026. First seen by Alion on Oct 17, 2026.
Overview
Company
Impact
Profile match
Tech Mahindra is a prominent Indian multinational information technology services and consulting enterprise specializing in digital transformation, cloud modernization, business process re-engineering, and network services. Headquartered in Pune, Maharashtra, India (with its registered office in Mumbai), the company is a flagship entity of the diversified Mahindra Group conglomerate. Established in 1986 (initially as Mahindra British Telecom), it operates across dozens of countries with a global delivery footprint serving enterprise clients in telecommunications, banking and financial services, healthcare, automotive, and retail. The organization is particularly recognized for its deep engineering heritage in telecommunications and 5G network integration, offering end-to-end solutions spanning artificial intelligence, enterprise application management, customer experience (CX), and next-generation connectivity infrastructure.
Backed by Seafund
Job Description
Skill Set :
AIOps
Total Experience :
7.00 to 10.00 Years
No of Openings :
1
Job Post Date :
04/08/2026
Job Expiry Date :
30/10/2026
Domain :
IT
Location :
PUNE [India]
Job Reference No :
4099580
Job Summary
(GCP Vertex AI, LangGraph, AWS with AIOps background)
Location-
Bengaluru/Pune/Mumbai/Noida/Kolkata/Hyderabad
- Design and lead implementation of enterprise Agentic AI platforms for IT Operations across Hybrid Cloud, Private Cloud, and On-Prem environments.
- Architect multi-agent systems including agents, orchestration, tools, policy layers, and execution frameworks.
- Define RAG/grounding architecture using enterprise knowledge sources (CMDB, runbooks, ITSM, documentation).
- Design guardrails including RBAC, human-in-the-loop approvals, audit logging, traceability, and rollback mechanisms.
- Integrate AI platform with ITSM, CMDB, observability, and automation platforms.
- Architect model gateway and LLM routing based on data sensitivity, cost, performance, and availability requirements.
- Implement hybrid model serving using self-hosted and cloud-based LLMs.
Lead architecture workshops, provide technical leadership, and enable customer ownership through knowledge transfer.
Must have -
- Agentic AI / Multi-Agent Architecture
- AI Platform Architecture
- Kubernetes / OpenShift
- Hybrid Cloud / Private Cloud Architecture
- RAG (Retrieval Augmented Generation)
- API Integration
- LLM Routing / Model Gateway
- Self-hosted & Cloud LLMs (vLLM, Azure OpenAI, Bedrock)
- RBAC & AI Guardrails
Good to have -
- ITSM / ServiceNow Integration
- CMDB Integration
- Observability Integration (Elastic, Splunk, Dynatrace, etc.)
- Human-in-the-Loop Workflow Design
- Experience across both self-hosted and cloud-hosted LLMs
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