Senior AI Solutions Architect

24 hours ago

Nellore, Andhra Pradesh, India beBeeMLOPS Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Description

Key Responsibilities:

  • We are seeking a seasoned MLOps professional to oversee the productionization of models, ensuring reliable services with clear SLOs, runbooks, and swift, safe rollbacks.
  • This role involves building automation-first delivery pipelines, reproducible builds, layered tests, and environment promotion using GitLab CI and Terraform-based IaC.
  • The ideal candidate will engineer scalable serving solutions, including batch and real-time inference on EKS/ECS/Lambda and Databricks Model Serving with probes, autoscaling, and canary/blue-green deployments.
  • Instrument end-to-end observability (data, model, system) and detect drift/regressions; lead incidents and post-mortems that drive durable fixes.
  • Promote collaboration across teams to translate requirements into designs, 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.

Requirements:

  • 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.

Benefits:
As an MLOps professional, you will have opportunities to collaborate with cross-functional teams and contribute to strategic planning.
You will also be part of an organization committed to promoting diversity, equity, and inclusion.

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