Senior Systems Engineer

Role overview

Senior Systems Engineer at Cornerstone OnDemand

Required qualifications

• 3–5 years of relevant experience Reports to: [Engineering Manager, Workforce AI]

Employment details

• Location: Hyderabad, India
• Employment type: Full-time (permanent) Level: Sr. System Engineer (mapped to experience)
• Shift: General shift, with periodic on-call rotation aligned to US time zones About the role We are hiring a System Engineer (level: System Engineer or Sr. System Engineer based on experience) to join Cornerstone's Workforce AI team in Hyderabad.
• You will work on platform-level feature development, data integrations, and end-to-end observability — building the cloud platform and frameworks that AI product teams across Cornerstone depend on every day.
• You will write real code in Java, Python, and Node.js, ship production infrastructure on AWS (EKS/ECS), and own the developer experience for the systems you build.
• This is a builder role on a small, high-trust platform team.
• You will ship production code and infrastructure, debug production issues with rigor, and be the kind of teammate others reach out to first.
• In this role you will...
• Drive platform-level feature development for Workforce AI — design and ship shared services, frameworks, and SDKs that AI product teams build on top of.
• Build and operate data integrations — pipelines, connectors, and event flows that move data between Workforce AI services and upstream/downstream systems (Cornerstone product data, customer tenants, AI/ML stores).
• Implement end-to-end observability — ship logs, metrics, and traces into ELK and Splunk; build dashboards, SLOs, and alert rules that catch real problems before customers do.
• Stand up, scale, and harden containerized workloads on Amazon EKS and ECS, including networking, autoscaling, secrets, and zero-downtime deploys.
• Implement CI/CD with Jenkins (and equivalents), enabling fast, safe delivery from commit to production across multiple services.
• Design and tune persistence layers on native databases (RDS / Aurora, DynamoDB, PostgreSQL, MySQL) — schema design, indexing, query and cost optimization.
• Write production code in Java, Python, and Node.js — clean, tested, well-documented modules that other engineers can build on.
• Build and maintain infrastructure-as-code in CloudFormation, Terraform, and Helm charts — repeatable, peer-reviewed, environment-parameterized.
• Partner with security, SRE, and Workforce AI product teams to set platform standards, document runbooks, and continuously improve developer experience.
• Triage and resolve incidents with rigor — reproduce, isolate, fix, and write blameless postmortems to prevent recurrence.
• You’ve got what it takes if you have… 3–5 years of relevant software / platform / infrastructure engineering experience.
• Hands-on AWS production experience — EKS and/or ECS, IAM, VPC, networking, S3, EC2, Lambda, RDS/DynamoDB.
• Proficiency in at least two of: Java, Python, Node.js — comfortable contributing real code, not just glue scripts.
• Strong CI/CD experience with Jenkins (or equivalents: GitHub Actions, GitLab CI, CircleCI).
• Working knowledge of Infrastructure-as-Code — CloudFormation, Terraform, and Helm charts in a production repo.
• Operational experience with ELK and/or Splunk — building dashboards, writing alert rules, debugging from logs.
• Solid grasp of relational and NoSQL databases (PostgreSQL/MySQL/Aurora, DynamoDB) — schema, indexes, query plans.
• Strong fundamentals: Linux, networking, containers (Docker), Git, code-review etiquette.
• Excellent problem-solving and communication — clear writing, calm under incident, generous with help to teammates.
• Nice to have AWS certifications (Solutions Architect Associate / DevOps Engineer Associate).
• Exposure to AI/ML platform components — model deployment, vector databases, GenAI infrastructure on AWS (Bedrock, SageMaker).
• Experience operating Kafka, RabbitMQ, or similar streaming/messaging systems.
• Service-mesh (Istio/Linkerd), API gateway, or platform-engineering exposure (Backstage, internal developer platforms).
• Cost & FinOps awareness — tagging strategies, rightsizing, savings plans.
• Security-conscious shipping — SAST/DAST, secrets management (Vault, AWS Secrets Manager), threat modeling. #LI-OnSite
• Location: Hyderabad [India]

About the employer

• Cornerstone OnDemand India Team: Workforce AI

Additional role details

• Sr. System Engineer — Workforce AI