2 days ago
Bengaluru, IndiaMid Level
Responsibilities
- Design, build, and operate the AI/ML platform on AWS and Kubernetes, including clusters, networking, IAM, storage, cost, and reliability.
- Provision and evolve infrastructure with Terraform using reviewed, rollback-capable infrastructure as code.
- Own CI/CD pipelines for data pipelines, ML models, and AI applications from repository through production.
- Build and evolve observability for metrics, logs, traces, dashboards, alerting, and SLOs.
- Automate environment provisioning, golden-path pipelines, and self-service tooling for data scientists.
- Partner with product, data science, and GenAI teams on model serving, evaluations, cost and latency controls, and safe rollouts.
- Deploy and operate AI agents and LLM workloads on Kubernetes, including autoscaling, GPU scheduling, secure egress, secrets, rate limits, and stateful sessions.
- Run proofs of concept, participate in code review and mentoring, and improve engineering processes.
Requirements
- At least 3 years of engineering experience in a complex technical environment.
- Deep hands-on production Kubernetes experience and hands-on AWS experience with at least three relevant AWS services.
- Working knowledge of Terraform modules, state, reviews, and drift management.
- Experience with Prometheus, Loki, Grafana, and/or Datadog for platform observability.
- Strong production Python and SQL skills.
- Experience building CI/CD pipelines and APIs end to end using GitHub, GitHub Actions, CodePipeline, or Jenkins.
- Hands-on production experience with AI/ML platforms, including data science tooling, model lifecycle, feature or inference infrastructure, and self-service enablement.
- Experience deploying AI agents or LLM workloads on Kubernetes.
- Working familiarity with modern agent frameworks, LLM serving, RAG or vector stores, LLM observability, and MCP.
- Preferred experience includes Bedrock AgentCore, Bedrock Agents, Bedrock Knowledge Bases, SageMaker, LangChain, LangGraph, Strands, Langfuse, LangSmith, Arize, OpenTelemetry GenAI, vLLM, KServe, Ray Serve, TGI, OpenSearch, pgvector, Pinecone, Kubeflow, MLflow, Snowflake, Bedrock Guardrails, and PII redaction.
Benefits
- Supportive senior team, global collaboration, and freedom to design and influence the platform.
- Opportunity to build AI/ML infrastructure supporting products used by patients, clinicians, and providers worldwide.
- Inclusive culture focused on excellence, individual expression, and innovative ideas.
Tech Stack
Apache AirflowAWSDatadogGitHub ActionsGrafanaJenkinsKubernetesMLflowPrometheusPythonSnowflakeSQLTerraform
Categories
About ResMed
We believe shaping a better world starts with better sleep and breathing, which is why we pioneer innovative solutions to help millions of people in more than 140 countries around the world live happier, healthier lives. Our AI-powered digital health solutions, cloud-connected devices and intelligent software make home healthcare more personalized, accessible and effective.