we are looking for a Senior DevOps Engineer with a strong software development background to build and evolve our internal DevOps platform. You will sit at the intersection of Platform Engineering, SRE, and MLOps - owning the infrastructure and tooling that powers production and enables our developers and data teams to move fast, safely, and with confidence.
If you believe DevOps should be a self-service platform, love automation, and naturally think in systems and end-to-end flows, keep reading.
What You Will Do:
Build a DevOps Platform (Platform-as-a-Product): Create internal services and golden paths that scale across teams (self-service over ad-hoc, repeatable over personal support).
Own CI/CD End-to-End: Design, build, and maintain Jenkins and GitHub Actions pipelines that move code from commit to production with high reliability, visibility, and safety.
Operate and Evolve Our AWS Stack: Hands-on ownership of AWS, including services such as ECS, EKS, Lambda, WorkSpaces, DynamoDB, Redshift, S3, DocumentDB (and the surrounding networking, IAM, observability, and deployment patterns).
Enable MLOps and Data Workflows: Support and automate ML and data pipelines using tools like Airflow, MLflow, and Jupyter Notebooks (plus integrations with compute, storage, and security controls).
Automation First: Eliminate manual work through Infrastructure-as-Code, scripting, and internal tooling. Build reusable components instead of one-off solutions.
Cost Optimization (FinOps): Drive cost visibility and optimization (tagging, budgets/alerts, rightsizing, workload efficiency, and practical trade-offs between cost and reliability).
Security Ownership: Bake security into pipelines and infrastructure (least privilege, secrets management, supply chain controls, vulnerability scanning, hardening, and incident readiness).
Leverage AI to Move Faster: Use AI tools such as Cursor, GitHub Copilot, and Claude Code to accelerate delivery (without compromising quality, security, or reliability).
Cross-Team Collaboration: Partner with Engineering, Data, and AI teams to unblock delivery, improve developer experience, and keep production stable.
Requirements: 5+ years hands-on experience in DevOps / SRE / Platform Engineering, ideally in a SaaS production environment.
Strong development background: You write code comfortably (not just scripts), build internal tools, and approach infra work with software engineering discipline (design, readability, testing, code review).
Proven experience with AWS, including ECS, EKS, Lambda, WorkSpaces, DynamoDB, Redshift, S3, DocumentDB.
Strong CI/CD experience with Jenkins, GitHub, and GitHub Actions (secure, reusable pipelines and good workflow hygiene).
Experience with ML/data tooling such as Airflow, MLflow, and Jupyter Notebooks.
Hands-on with AI-assisted development tools (Cursor, GitHub Copilot, Claude Code) and a pragmatic approach to using them effectively.
Demonstrated cost optimization experience (FinOps mindset, measurement, and continuous improvement).
Demonstrated security experience (cloud security fundamentals, IAM, secrets, secure SDLC, and operational security).
A wide-angle thinker: you naturally see the whole system, understand dependencies, and build solutions that scale across teams.
Strong communication and collaboration skills.
This position is open to all candidates.