Senior Backend Engineer

There are two Back End roles here, both sitting within the same product-led SaaS environment, but with slightly different focus areas. Both are senior, hands-on positions in a brownfield setup, so the emphasis is on improving and extending existing systems rather than building from scratch.

Role 1 - core Back End/platform services

This role sits within the core Back End platform team. The work is centred around maintaining and evolving existing Go services that underpin the product.

What you'll be doing

Working on production Go services, improving performance, reliability and maintainability Owning features end to end from product requirements through to implementation Designing and evolving PostgreSQL schemas, writing efficient queries and handling migrations safely in a live environment Contributing to a distributed, event-driven architecture using Kafka or similar Deploying and running services via Docker and Kubernetes in AWS Working with a fair degree of autonomy where product requirements are defined but technical approach is not always prescribed

What matters for this role

Strong experience in brownfield Go environments, not just greenfield builds Deep understanding of PostgreSQL in production systems Solid grasp of microservices and event-driven patterns Ability to make pragmatic engineering decisions without heavy oversight Comfortable using AI coding tools as part of your workflow, but able to validate and iterate on outputs properly

Nice to have here includes exposure to Temporal for workflows, Twilio integrations and additional Back End languages such as Node.js or TypeScript.

This is the more "traditional" Back End role, focused on platform stability, scalability and ongoing product evolution.

Role 2 - AI/agentic systems

This role is more focused on building out newer AI-driven capabilities within the platform. It still requires strong Go fundamentals, but the work is more exploratory and centred around agent-based systems.

What you'll be doing

Building and integrating agents, agentic tooling and MCP-style Servers into the existing platform Prototyping and iterating quickly on AI-driven features, then hardening them for production use Working from loosely defined problems, evaluating different approaches and selecting the most effective solution Integrating with existing Back End services and data layers, including PostgreSQL Using AI coding agents heavily to accelerate development and delivery

What matters for this role

Strong Go experience in real-world systems, again with a focus on existing services rather than greenfield only Practical experience building or working with agents or agent-based tooling Comfort operating in ambiguity, where problems are not fully defined upfront Ability to move quickly from idea to working solution, then iterate Sensible use of AI tooling - fast, but with proper validation and engineering judgement

Nice to have includes exposure to AgentCore, some Python or Node.js and any Front End exposure such as

Strong experience in brownfield Go environments, not just greenfield builds Deep understanding of PostgreSQL in production systems Solid grasp of microservices and event-driven patterns Ability to make pragmatic engineering decisions without heavy oversight Comfortable using AI coding tools as part of your workflow, but able to validate and iterate on outputs properly

Nice to have here includes exposure to Temporal for workflows, Twilio integrations and additional Back End languages such as Node.js or TypeScript., Strong Go experience in real-world systems, again with a focus on existing services rather than greenfield only Practical experience building or working with agents or agent-based tooling Comfort operating in ambiguity, where problems are not fully defined upfront Ability to move quickly from idea to working solution, then iterate Sensible use of AI tooling - fast, but with proper validation and engineering judgement

Nice to have includes exposure to AgentCore, some Python or Node.js and any Front End exposure such as

This role is more focused on building out newer AI-driven capabilities within the platform. It still requires strong Go fundamentals, but the work is more exploratory and centred around agent-based systems.