Senior Architect

Department Icon Data Science Analytics & Machine Learning
Posted: 3 months ago
10-12 years
Bengaluru / Bangalore, Karnataka
Data Science Analytics & Machine Learning
work from office
Full Time

Posted: 3 months ago
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Posted over 15 days ago, so the role may have closed. Confirm on the employer's page when you apply, or see similar jobs.

Job Description

  • Hello All,
  • #Immediate Job Hiring - #SeniorAIArchitect (10+ YOE)
  • Job location: Bangalore, Hyderabad, Pune, Mumbai
  • Work Mode: Hybrid
  • Notice: Immediate to 15 days

The Role

Define and document the governance, observability, and Human-in-the-Loop operating model for the agentic platform, translating customers GRC policies into enforceable guardrails, RBAC, audit trails, escalation workflows, and dashboards used in deliverable acceptance walkthroughs.

Must-Have

  • 10+ years in enterprise architecture; 3+ years on Gen-AI/AI/ML governance, Responsible AI, or model-risk programs
  • Hands-on with at least three of: Azure AI Content Safety, Azure Purview, Microsoft Defender for Cloud, Entra ID (RBAC/Conditional Access), Azure Monitor + Log Analytics, Application Insights/OpenTelemetry
  • LLM observability tooling exposure: Azure AI Foundry Evaluations, or equivalent
  • Reliability patterns for multi-step agent workflows: timeouts, retries, circuit breakers, idempotency keys, fallback routes, dead-letter queues
  • HITL workflow design using Microsoft Teams approvals, Adaptive Cards, oe Power Automate; ability to spec escalation triggers and SLAs
  • Governance documentation: runbooks, operating guides, and playbooks

Good to Have

  • Hands-on enterprise compliance/ethics review (not just advisory)
  • Prior Microsoft Foundry governance blueprint authoring

Key Responsibilities

  • Author the governance + HITL operating model: monitoring, logging, bias/drift detection, escalation matrices, audit evidence, and runbooks
  • Define RBAC (Entra ID groups, Snowflake roles), policy guardrails, and ethical safeguards across agentic workflows
  • Design reliability patterns for multi-step agent workflows (timeouts, retries, and fallbacks) and reflect these in architecture artifacts and runbook guidance
  • Drive deliverable acceptance through walkthroughs, dashboards, and traceable evidence within the 10-business-day Acceptance Review Period
  • Partner with customers governance, risk, and compliance stakeholders to translate policies into practical guardrails and documented controls

Please share your updated CV to [HIDDEN TEXT]

Skills

SnowflakeAi/mlAnalyticsAiMl

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