Description

Key Responsibilities

Design, build, and operate scalable, production-grade platforms following DevOps best practices
Analyze production environments, identify systemic issues, and drive engineering improvements to enhance production stability and supportability
Develop and manage Infrastructure as Code (IaC) using tools such as Terraform and CloudFormation
Architect and implement CI/CD pipelines for both application and ML workloads with a focus on automation and reliability
Design, develop, and maintain backend services and RESTful APIs using Java and Spring Boot
Collaborate with cross-functional teams including data science, engineering, and operations to improve production readiness and reduce operational overhead
Manage and optimize containerized workloads using Kubernetes (EKS/ECS)
Implement consistent configuration management across environments (dev, QA, staging, prod)
Establish monitoring, logging, and observability frameworks (Dynatrace preferred) to proactively detect issues and drive continuous improvements
Integrate automated testing, security scans, and compliance checks into CI/CD pipelines
Support ML engineers and data scientists in building and operationalizing ML workflows
Continuously improve platform reliability, scalability, and performance through engineering solutions rather than manual production support activities

Required Skills & Qualifications

Strong experience with DevOps practices for building and operating production systems
Proven ability to analyze production issues and implement long-term engineering solutions to reduce incident volume and improve system resilience
Hands-on expertise with Infrastructure as Code tools (Terraform, AWS CloudFormation)
Proven experience in CI/CD pipeline design, automation, and optimization
Proficiency with Git-based workflows (Git, Gitflow, branching and release strategies)
Advanced experience with Kubernetes orchestration (AWS EKS/ECS preferred)
Strong experience in Java development using Spring Boot / Spring Framework
Strong understanding of RESTful API design and microservices architecture using Spring
Experience building, deploying, and scaling Java-based backend services in cloud environments
Strong understanding of AWS cloud services and cloud-native architecture patterns
Experience with configuration and environment management practices
Solid experience in monitoring and observability tools (Dynatrace preferred), with focus on actionable insights
Familiarity with integrating automated testing, security, and compliance into pipelines
Solid Linux/Unix administration skills
Basic understanding of networking fundamentals (DNS, VPCs, load balancers, security groups)
Working knowledge of TLS/SSL certificate lifecycle management
Understanding of software design patterns and clean architecture principles

Preferred / Nice-to-Have Skills

Exposure to ML engineering and MLOps workflows (model training, deployment, monitoring)
Experience collaborating closely with data science teams
Prior experience with Dataiku deployed on EKS
Experience running Java Spring Boot applications on Kubernetes (EKS/ECS)
Platform engineering or internal product-building mindset
Experience improving operational excellence through automation and system design rather than manual support

Key Skills

Education

Bachelor's or Master's degrees