Ops / SRE Support Engineer – VLabs - Manager

We are seeking an experienced AI Architect to lead the design, development, and governance of enterprise-grade AI and AIOps solutions across cloud-native environments. This role will define the architecture for Generative AI, agentic systems, and intelligent operations platforms on Microsoft Azure, ensuring scalability, reliability, security, and responsible AI adoption.

The ideal candidate combines deep expertise in GenAI, Agentic Harness, Agentic Engineering, AI/ML systems, distributed architectures, observability, and cloud engineering, with hands-on experience building production-grade GenAI and AIOps solutions. You will play a critical role in shaping AI strategy, establishing architectural standards, and enabling teams to deliver high-impact, enterprise AI capabilities . You will be able to think at system and platform level, not just application level , t ranslate complex AI capabilities into scalable enterprise solutions whilst balancing innovation with reliability, security, and governance .

Define end-to-end architecture for Generative AI, agentic systems, and AIOps platforms

Design scalable, secure, and resilient AI systems across cloud and hybrid environments

Establish reference architectures, design patterns, and best practices for AI systems

Architect multi-agent systems, orchestration workflows, and tool integration frameworks

Define patterns for RAG, retrieval pipelines, and knowledge integration

Design evaluation frameworks, guardrails, and Responsible AI controls

Guide implementation of agent frameworks and workflow orchestration

Design patterns for implementation with Agentic Harness

Architect intelligent operations platforms leveraging logs, metrics, traces, and events

Define strategies for anomaly detection, alert correlation, and automated remediation

Establish observability standards using Open Telemetry (OTEL) and modern monitoring tools like Tempo , Loki , Prometheus , Grafana , etc.

Lead architecture for AI solutions on Microsoft Azure

Design cloud-native systems using containers (Docker, Kubernetes)

Define data architecture across PostgreSQL, Cosmos DB, SQL Server, and telemetry pipelines

Guide teams on backend architecture using Python and FastAPI

Define CI/CD, DevOps, and automation strategies using ADO and GitHub

Establish standards for testing, evaluation, and performance optimization of AI systems

Define enterprise standards for AI security, privacy, and compliance

Implement Responsible AI practices including:

Prompt safety

Data protection

Access control

Model governance

Ensure auditability and reliability of AI-driven systems

Drive improvements in MTTR, MTTD, reliability, and operational efficiency

Define SLIs, SLOs, and error budgets for AI-powered services

Architect automation for incident response and root-cause analysis

Partner with SRE, platform, data, and application teams

Mentor engineers and guide architectural decision-making

Influence AI strategy and roadmap across the organization

Apply s trong communication and stakeholder management skills

Location: Bangalore

We are an equal opportunity employer that does not discriminate on the basis of any legally protected status.

Please note, AI is used as part of the application process.