Chief AI Systems Architect

7 days ago

Chennai, Tamil Nadu, India beBeeMachineLearning Full time ₹ 20,00,000 - ₹ 25,00,000

Job Opportunity

  • Design and develop scalable machine learning systems in production to drive business outcomes.

Key Responsibilities

Transform models from tracked experiments into governed releases, ensuring resilient services with clear Service Level Objectives (SLOs), runbooks, and fast, safe rollbacks.
Build automation-first delivery pipelines using GitLab CI and Terraform-based Infrastructure as Code (IaC) for reproducible builds, layered tests, and environment promotion.
Engineer scalable serving architectures for batch and real-time inference on Amazon Elastic Container Service (ECS) and Amazon Elastic Container Service for Kubernetes (EKS) with probes, autoscaling, and canary/blue-green deployments.
Instrument end-to-end observability (data, model, system); detect drift/regressions; lead incidents and post-mortems that drive durable fixes.

Collaborate across teams to translate requirements into designs, Architecture Decision Records (ADRs), and change plans; balance security, privacy, cost, and performance tradeoffs.
Continuously reduce toil through automation, optimize model/GPU/LLM cost, and evolve templates/playbooks for repeatable delivery.

Required Skills and Qualifications:

  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related field and 3+ years of relevant experience as outlined in the key responsibilities; or High School Diploma/General Education Degree and 6+ years of relevant experience as outlined in the key responsibilities in lieu of Bachelor's Degree.
  • 3+ years operating ML systems in production (MLOps).
  • Experience with Python for ML engineering (packaging, typing, testing, performance)
  • Experience developing GitLab CI for ML/GenAI (multi-stage pipelines, artifacts, evaluation/security gates) and Terraform for ML/GenAI (reusable modules, drift detection); secure packaging & containerization.
  • Experience deploying and operating compute for ML (EKS/ECS/Lambda), and secure data access patterns (S3/VPC/IAM/KMS, private endpoints)
  • Experience implementing MLflow tracking, model registry & governed promotion, packaging & deployment to multi-target runtimes.
  • Experience operating real-time + batch/streaming inference workloads, ML observability, layered testing (unit/integration), workflow orchestration, and cost optimization.
  • Experience designing and implementing IAM least-privilege, secrets/key management for CI/CD pipelines; privacy and compliance awareness.

Preferred Qualifications:

  • Advanced GitLab CI (dynamic child pipelines, components, cross-project triggers, security scans, compliance gates).
  • Advanced Terraform (policy-as-code, gated plan/apply, environment promotion).
  • Advanced real-time serving (multi-tenant routing, dynamic model loading) and SLO-driven rollback/automation.
  • Databricks governance (Unity Catalog, lineage) and feature platform approval/reuse workflows.

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