Backend Engineer

We are looking for strong Backend Engineers to build enterprise platforms and deliver application modernisation using our Enterprise Coding Platform (Software Factory). Our work spans Agent Platform, ML Platform, Data Platform, and Ontology and Context Platform, alongside the Software Factory that accelerates enterprise software delivery.

As an FDE - Backend Engineer, you will work across platform development, enterprise integrations, re-architecture, and modernisation. You will use the Software Factory to deliver working software, identify gaps encountered during delivery, and turn those lessons into reusable improvements that help other engineers and teams move faster.

This is a backend engineering role across multiple products and enterprise projects. Your allocation may change based on priorities, delivery needs, and your strengths. You should be comfortable learning unfamiliar systems and owning work from understanding requirements through implementation, testing, deployment, and production support.

Responsibilities:

• Enterprise Coding Platform / Software Factory: Backend services, integrations, and workflows that connect requirements, architecture, code generation, testing, code review, and deployment within enterprise SDLC processes.
• Agent Platform: Services for agent execution, tool integration, workflow orchestration, enterprise connectivity, and operational visibility.
• ML Platform: Backend capabilities supporting model workflows, deployment, evaluation, and integration with enterprise applications.
• Data Platform: APIs, connectors, ingestion and processing workflows, and services that make enterprise data accessible to applications and agents.
• Ontology and Context Platform: Services for managing business concepts, relationships, metadata, and contextual knowledge, and exposing them to agents and applications.
• Enterprise modernisation: Understanding existing applications, redesigning service boundaries, re-engineering data access and APIs, replacing legacy integrations, and delivering changes across interconnected systems.
• Build backend services: Design, implement, and maintain APIs, business logic, and shared services across platform products and enterprise applications.
• Deliver modernisation work: Understand existing codebases, trace dependencies and business behaviour, and implement re-architecture and modernisation changes while preserving required functionality.
• Integrate enterprise systems: Connect internal applications, third-party platforms, and business systems through APIs, webhooks, messaging, and background jobs.
• Build reusable components: Develop connectors, adapters, and shared libraries with authentication, data mapping, validation, and error handling.
• Implement reliable workflows: Handle timeouts, retries, idempotency, failure recovery, reconciliation, and asynchronous processing.
• Apply the Software Factory: Use AI-assisted and agentic development workflows for codebase exploration, implementation, testing, debugging, and review, while remaining accountable for correctness and quality.
• Improve the Software Factory: Identify recurring delivery bottlenecks and contribute improvements to its backend services, integrations, templates, tools, context, and automated validation.
• Accelerate enterprise SDLC: Integrate Software Factory capabilities into existing repositories, issue tracking, review processes, test suites, and CI/CD pipelines.
• Own delivery end to end: Take responsibility for assigned services and features from requirements and design through implementation, testing, deployment, monitoring, and issue resolution.
• Validate connected systems: Write automated tests, verify API contracts, and troubleshoot failures across services, data flows, and environments.
• Collaborate across teams: Work with product owners, architects, domain experts, and engineers to clarify requirements, resolve dependencies, and make practical engineering decisions.
• Turn project learning into platform improvements: Document useful patterns and convert repeated solutions into capabilities that can be reused across products and projects.

Requirements:

• Backend programming: Strong skills in Python or TypeScript/JavaScript, with hands-on experience developing backend services and REST APIs.
• Integration engineering: Experience connecting applications or systems, including authentication, request/response mapping, validation, and handling integration failures.
• Software design: Good working understanding of object-oriented programming, abstraction, encapsulation, interfaces, and composition, with the ability to structure modular, maintainable code.
• API fundamentals: Understanding of HTTP, JSON, API contracts, status codes, pagination, and versioning.
• Databases: Practical experience with SQL, relational databases, schema design, and transactions.
• Asynchronous workflows: Understanding of background jobs, messaging, retries, and reliable processing across service boundaries.
• Security: Understanding of authentication, authorisation, tokens, service credentials, and application permissions.
• Existing codebases: Ability to navigate unfamiliar applications, investigate dependencies, understand existing behaviour, and make reliable changes.
• Engineering practices: Experience with Git, code reviews, automated testing, and systematic debugging, along with exposure to CI/CD and application deployment.
• Agentic AI and MCP familiarity: Basic understanding of agents, tool calling, and Model Context Protocol, including how agents interact with APIs and backend systems. Exposure through professional work, personal projects, or experimentation is welcome.
• AI-assisted development: Willingness to use coding assistants and agents, critically review generated changes, and validate their behaviour through testing.
• Ownership and adaptability: Ability to work across products and project contexts, communicate clearly, investigate issues independently, and own outcomes through deployment.

Useful experience — you do not need all of these:

• Backend frameworks and runtimes: FastAPI, Django, Node.js, or equivalents.
• Enterprise applications: CRM, ERP, identity providers, billing, order management, inventory systems, or other business platforms.
• Modernisation and re-architecture: Legacy application analysis, service decomposition, API redesign, database migrations, integration replacement, or incremental migration.
• Integration patterns: Webhooks, event-driven processing, scheduled synchronisation, batch integrations, and workflow orchestration.
• Messaging: Kafka, RabbitMQ, SQS, SNS, EventBridge, or equivalent technologies.
• Data: PostgreSQL, MySQL, Redis, DynamoDB, query optimisation, and data processing pipelines.
• Context and ontology: Metadata services, knowledge graphs, semantic models, search, retrieval, or APIs that expose business context to applications and agents.
• Agent and ML platforms: Model APIs, MCP servers/clients, agent frameworks, model-serving APIs, evaluation workflows, or execution monitoring.
• AWS: ECS/Fargate, Lambda, API Gateway, S3, RDS, IAM, Secrets Manager, and CloudWatch. Relevant Azure or GCP experience is also welcome.
• Containers and orchestration: Docker and Kubernetes, including containerizing applications, configuration, and deployment troubleshooting.
• Testing: Robot Framework, Playwright, BDD scenarios written in Gherkin, and API, contract, integration, and end-to-end testing.
• GitLab and CI/CD: Repositories, merge requests, and pipelines for automated builds, tests, and deployments. Experience with GitHub Actions, Jenkins, or similar tools is also relevant.
• Infrastructure as code: Basic understanding of Terraform, including reading and modifying existing configurations and reviewing infrastructure plans.
• Security and reliability: OAuth2/OIDC, JWT validation, RBAC, least-privilege access, audit logging, monitoring, tracing, and production troubleshooting.
• Developer productivity: Building reusable templates, SDKs, CLI tools, development automation, or integrations that improve engineering workflows.

What success looks like:

• You deliver reliable backend capabilities across enterprise platforms and modernisation projects, take ownership through deployment, and use the Software Factory effectively to accelerate delivery.
• Your work also improves the factory itself, making recurring engineering tasks easier, faster, and more reliable for the next team and project.

Skills

API, DynamoDB, HTTP, JSON, JavaScript, MySQL, Node.js, PostgreSQL, Python, REST, Redis, SQL, TypeScript