AI SRE

7 days ago

Bengaluru, Karnataka, India Tata Consultancy Services Full time ₹ 15,00,000 - ₹ 30,00,000 per year

TCS has been a great pioneer in feeding the fire of young techies like you. We are a global leader in the technology arena and theres nothing that can stop us from growing together.

What we are looking for

Role: AI SRE (Docker,kuberenetes,Ansible)

Experience Range: 6 – 8 Years

Location: Bangalore

Must Have:

  • Production experience in SRE / Infrastructure / ops for large-scale systems
  • Strong programming/scripting skills (Python, Go, Java, or equivalent)
  • Deep experience with containerization (Docker), orchestration (Kubernetes, etc.)
  • Infrastructure-as-code (Terraform, Helm, CloudFormation, Ansible, etc.)
  • Familiarity with GPU / AI compute clusters, high-performance data storage, and distributed architectures
  • Experience with monitoring / observability / logging / alerting tools (Prometheus, Grafana, ELK / EFK, Datadog, etc.)
  • Networking & systems engineering knowledge (TCP/IP, DNS, routing, load balancing, distributed storage)
  • Solid experience in capacity planning, performance tuning, scaling, and incident response
  • Demonstrated ability to lead RCAs, deploy fixes, and drive reliability improvements
  • Experience in regulated environments (financial services, compliance, audit, security) is a strong plus
  • Excellent communication, documentation, and cross-team collaboration skills
  • Proven track record of reducing operational toil via automation

Good to Have:

  • Understanding of SRE techniques.
  • Proficiency with Open Telemetry tools including Grafana, Loki, Prometheus, and Cortex.
  • Good knowledge of Microservice based architecture, industry standards, for both public and private cloud.
  • Knowledge of data pipeline technologies (Kafka, Spark, Flink, etc.)
  • Good knowledge of various DB engines (SQL, Redis, Kafka, Snowflake, etc) for cloud app storage.
  • Experience working with Generative AI development, embeddings, fine tuning of Generative AI models.
  • Experience in high-performance computing (HPC), distributed GPU cluster scheduling (e.g. Slurm, Kubernetes GPU scheduling)
  • Understanding of ModelOps/ ML Ops/ LLM Op.
  • Experience with chaos engineering, canary deployments, blue/green rollouts

Essential:

  • Operate, monitor, and maintain the infrastructure supporting GenAI applications (training, inference, feature store, data ingestion, model serving)
  • Design and build automation for core platform capabilities, reducing manual toil
  • Develop and maintain infrastructure-as-code (IaC) for provisioning and managing compute, storage, network, GPU clusters, Kubernetes / container orchestration, etc.
  • Establish, monitor, and enforce SLOs/SLIs/SLAs, error budgets, alerting, and dashboards
  • Lead incident response, root cause analysis (RCA), postmortems, and systemic remediation
  • Perform capacity planning, scaling strategies, workload scheduling, and resource forecasting
  • Optimize cost vs. performance tradeoffs in large-scale compute environments
  • Harden systems for security, compliance, auditability, and data governance
  • Collaborate across teams (cloud engineers, data engineers, infrastructure, security) to ensure safe deployment, rollout, rollback, and integration of new systems
  • Define disaster recovery (DR) strategies, backup/restore practices, fault tolerance mechanisms
  • Maintain runbooks, operational playbooks, documentation, and training materials
  • Participate in on-call rotations and respond to production incidents 24/7 as needed
  • Continuously evaluate and integrate new tools, frameworks, or technologies to enhance platform reliability

Minimum Qualification:

  • 15 years of full-time education
  • Minimum percentile of 50% in 10th, 12th, UG & PG (if applicable)

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