17 of 17 Amazon S3 Jobs in the City of London

data modelling AI/ML : OpenAI integration, semantic search, conversational agents, unstructured data analysis and extraction Infrastructure : AWS (Lambda, ECS/EKS, API Gateway, S3) DevOps : Terraform, GitHub Actions, Helm, Infrastructure-as-Code Data Science : Graph analytics, data pipelines, ETL workflows, Jupyter notebooks Required Qualifications Software Development 5+ years ...

particularly Apache Airflow. Experience with model registries and experiment tracking platforms (MLflow preferred). Experience deploying and operating ML workloads on AWS (Batch, EC2, S3, IAM, CloudWatch). Solid understanding of the ML lifecycle: training, evaluation, deployment, monitoring, and retraining. Experience with containerisation (Docker) and infrastructure-as-code. Proficiency ...

products reliably in production. What you'll do Design, build, and operate cloud-native AI platform infrastructure across AWS (Lambda, API Gateway, DynamoDB, S3, CloudWatch) and Databricks Deploy and operate containerised services on Kubernetes using Terraform for infrastructure-as-code Own and scale vector search infrastructure (OpenSearch, Algolia ...

Knowledge of REST APIs and cloud integrations Exposure to multi-cloud environments including Azure and Oracle Cloud preferred Experience with AWS services including EC2, S3, Lambda, VPC, and IAM Experience with CI/CD and automation platforms such as GitHub Actions and Azure DevOps Exposure to Azure services including ...

Airflow, Dagster or other Proficiency in one or more programming languages: Python, Java, GO or other Experience with AWS or GCP and their products (S3, GCS, Kinesis, Pub/Sub, Lambda/Cloud functions, DataProc) Experience with one of the main databases for analytics (Redshift, BigQuery, Snowflake or other ...

cloud-scale operations What we’re looking for Strong experience building and running production systems on AWS Deep familiarity with services like Lambda, DynamoDB, S3, EC2, SQS, EventBridge, CloudWatch, and Route 53 Excellent Python skills, plus experience with Go for high-performance tooling or services Experience with infrastructure ...

them clearly for team adoption Leadership mentality: Comfortable setting standards and directing technical decisions, not just executing them Technologies We Use Cloud: AWS (CDN, S3, IAM) Compute: Bare metal servers, Kubernetes (transitioning from bare metal) Networking: Tailscale/Wireguard for mesh topology, zero-trust architecture CI/CD: CircleCI ...

Hands-on experience deploying applications on Red Hat OpenShift and/or Kubernetes. Strong cloud experience with AWS services such as ECS, EKS, Lambda, S3, etc. Solid understanding of MongoDB and NoSQL design patterns. Prior experience in Payments Processing, financial services, or banking systems. Strong communication skills ...

Apply best practices around data quality, governance, and performance optimisation. Required Skills & Qualifications: Strong hands-on experience with AWS Data Engineering stack (e.g., Glue, S3, Lambda, Redshift, Athena). Advanced SQL skills. Proficiency in Python for data processing and pipeline development. Infrastructure/tooling exposure (e.g., Terraform, APIs ...

alongside practical exposure to AI/ML concepts or tools. You must have strong hands-on experience in: AWS Data Engineering stack (e.g. Glue, S3, Lambda, Redshift, Athena) SQL (advanced level) Python (for data processing and pipeline development) Infrastructure/tooling exposure (e.g. Terraform, APIs, CI/CD beneficial ...

most of the following: Frontend: TypeScript, Astro and/or Next.js, React, HTML, CSS Backend: Node.js, Go, RESTful APIs, OpenAPI Cloud: AWS, Lambda, DynamoDB, S3, CloudFront Infrastructure as Code: SST, Terraform, CDK, Pulumi or similar Testing: integration and end-to-end testing, component story testing, and visual regression testing ...

backend development within an enterprise level organization Extensive experience coding and deploying features within AWS serverless environment Experience working with AWS Services Lambda, S3, DynamoDB Observability tools such as Datadog or NewRelic ...

platforms: Prompt engineering Context management Workflow design for scalable automated code generation in regulated environments Strong hands-on experience with AWS ecosystem: AWS Glue, S3, and related data platforms (e.g. Snowflake) Strong experience with Apache Airflow and DAG-based orchestration Experience designing configuration-driven frameworks: Using YAML or JSON ...

Reporting Framework Add instrument and asset class coverage in our Trade Repository system Manage data exchange with third-party vendors via SFTP and AWS S3 Use AI coding assistants (Claude, Cursor, GitHub Copilot) to compress delivery timelines while maintaining full code ownership and quality accountability Collaborate with quant researchers … years in financial services (buy-side strongly preferred) Solid relational database skills; MS SQL Server a strong plus Snowflake experience required Familiarity with AWS (S3, Lambda, EC2, Glue or similar) Proficiency with Git, CI/CD pipelines, and observability tooling (e.g. Datadog) AI & Tooling: Proven, hands-on experience shipping ...

What You’ll Be Working On Building and supporting APIs and microservices in production Developing backend systems using Python + AWS (Lambda, API Gateway, S3, DynamoDB) Working with event-driven systems (Kafka, SNS/SQS, etc.) Supporting and improving existing production systems Debugging real-world issues and keeping systems … stable at scale Collaborating within an existing team + codebase (pragmatic engineering) Tech Stack Python AWS (Lambda, API Gateway, S3, DynamoDB, IAM) Event-driven systems (Kafka, SNS/SQS) Databases (Postgres, DynamoDB, Couchbase) CI/CD (Concourse, Git workflows) Observability (Prometheus, Grafana, CloudWatch) What You’ll Bring Strong backend ...

ecosystem. What You’ll Be Working On Designing and delivering scalable APIs and microservices Building backend systems using Python + AWS (Lambda, API Gateway, S3, DynamoDB) Handling event-driven architectures (Kafka, SNS/SQS, etc.) Driving system design decisions across distributed systems Improving observability, reliability, and performance in production … Debugging complex issues and leading resolution across teams Staying hands-on while setting technical direction and standards Tech Stack Python AWS (Lambda, API Gateway, S3, DynamoDB, IAM) Event-driven systems (Kafka, SNS/SQS) CI/CD (Concourse, Git workflows) Databases (Postgres, DynamoDB, Couchbase) Observability (Prometheus, Grafana, CloudWatch) What ...

Our client is a high-performing market-maker & liquidity provider. The business is expanding its London engineering team due to continued commercial growth and increasing demand across its trading operations. This role involves working on ...