Associate Tech Lead, DevOps
About the role
The Associate Tech Lead, DevOps at LSEG's Digitalisation Centre of Excellence is a hands-on engineering role focused on building, operating, and improving platforms, pipelines, and operational foundations for data, analytics, machine learning, and AI systems in production. The position emphasizes AWS, Kubernetes/EKS, DevOps, platform reliability, CI/CD, infrastructure-as-code, observability, security controls, and incident readiness. The role collaborates closely with Machine Learning and AI Engineers to ensure production systems are deployable, observable, secure, and maintainable. Responsibilities include designing and operating CI/CD pipelines, managing infrastructure-as-code, ensuring operational readiness, supporting AWS event-driven architectures, and enabling MLOps and AI productionisation. The team operates on a hybrid workstyle with a standard UK shift to support global operations. LSEG offers a collaborative environment, opportunities for growth, and a range of tailored benefits.
Must have
- 5-6 years of experience in DevOps or Platform Engineering roles.
- Experience designing and operating CI/CD pipelines, preferably using GitLab CI/CD, for backend, data, ML and containerised services.
- Practical experience with infrastructure-as-code, preferably Terraform, with exposure to Terragrunt or reusable environment orchestration patterns.
- Strong understanding of Linux, networking, and AWS cloud environments.
- Experience with monitoring, logging, tracing, dashboards and alerting for production systems, using tools such as OpenTelemetry, DataDog, Grafana/Prometheus, Sentry or PagerDuty where appropriate.
- Strong hands-on experience deploying, operating, and troubleshooting containerised workloads on Kubernetes, preferably AWS EKS.
- Experience managing EKS workloads, including deployment patterns, scaling, worker node sizing, resource management, and operational troubleshooting.
- Practical experience with AWS serverless and event-driven services, including Lambda, S3, SQS, API Gateway, IAM and Secrets Manager.
- Ability to collaborate effectively with ML and AI engineers on production workloads.
Nice to have
- Exposure to MLOps patterns, including model packaging, model/service deployment, artefact versioning, inference endpoints, monitoring hooks and retraining workflows.
- Support reusable deployment patterns for ML/AI workloads, including SageMaker endpoints, containerised inference services and integration with observability controls.
- Exposure to operating AI/LLM services in production, including AWS Bedrock or similar managed AI platforms.
- Familiarity with AWS SageMaker or similar ML platforms.
- Experience supporting data pipelines (Spark, batch/streaming jobs).
- Knowledge of secure cloud engineering patterns.
- Experience working in regulated or high‑reliability environments.
- Experience with tools such as Semgrep, Trivy, Checkov, Open Policy Agent, TFLint, Infracost, GuardDuty or equivalent.
- Experience with container registries and artefact repositories such as AWS ECR and Artifactory.
- Exposure to GitOps deployment patterns, Flux, Argo CD or equivalent.
Technologies
- Agile
- Artifactory
- AWS
- Amazon Bedrock
- AWS CDK
- CI/CD
- CloudFormation
- Data Pipelines
- Data Science
- Datadog
- DevOps
- DynamoDB
- EKS
- Event-Driven Architecture
- Feature Engineering
- Flux
- GitLab
- GitOps
- Grafana
- IAM
- Infrastructure as Code
- Kubernetes
- AWS Lambda
- Linux
- LLM
- Machine Learning
- MLOps
- Observability
- OpenTelemetry
- PagerDuty
- Prometheus
- S3
- SageMaker
- SAST
- Sentry
- Serverless
- Spark
- SQS
- Terraform
Highlights
The role follows a hybrid workstyle (3 days in office) and operates on the Standard UK Shift (12:30 PM to 9:30 PM Sri Lankan Time). LSEG offers benefits such as healthcare, retirement planning, paid volunteering days, and wellbeing initiatives. The company values diversity and is an equal opportunities employer. Application details are not specified in the listing.
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