Backend Dev & Infrastructure DevOps Engineer

Overview

This role merges backend/serverless data engineering with cloud infrastructure one person who owns the data layer and also owns containerization and load balancing. You implement the persistence and data-access layer the architect specs (potentially different databases per client, depending on the architect's decision), wire in authentication, and make the whole thing deployable, observable, and resilient against a 99.95% uptime target. If the platform runs on AWS, this role lives in Lambda day to day, using Amazon's own APIs for data access; on Azure, the equivalent serverless/data-access stack applies.

What You'll Build

• Serverless backend functions end-to-end (AWS Lambda, or Azure Functions if that's the chosen provider) daily-driver work, not occasional serverless
• Data access layer against per-client databases (Mongo and/or SQL, per architecture decision) using the cloud provider's native APIs
• Authentication/authorization implementation
• Silo enforcement no client's data path touches another's
• Containerization strategy (Docker/ECS/EKS or Azure equivalent)
• Load balancing configured per client where required
• CI/CD, observability, and failover engineered to hit 99.95% uptime, with a costed path to 99.99% if the business wants it later

Must Have

• 6+ years backend/infrastructure, including 2+ years building on AWS Lambda or Azure Functions in production at volume, and hands-on container orchestration in production
• Comfortable in Java, Python, or Go (explicitly not Node.js)
• Experience with both document (MongoDB/DynamoDB) and relational (SQL) persistence
• AWS or Azure load-balancing and multi-tenant deployment experience
• Financial-services or other high-compliance backend/infra experience
• Has actually owned an uptime SLA in the 99.9 99.99% range and can explain the architecture tradeoffs at each tier, not just repeat high availability back to you