AI SRE (Docker,kuberenetes,Ansible)

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)