Full Stack Engineer

Software Engineer / Senior Software Engineer Backend & Integration Engineering

Company: Physarum Software

Openings: Approximately 30 across experience levels

Experience: Typically 3-10 years; strong candidates outside this range are welcome.

Physarum builds enterprise applications and platforms spanning cloud services, data and agentic AI. We are looking for strong backend engineers with practical experience integrating applications, services and enterprise systems.

You should be comfortable building APIs, connecting systems, handling data and asynchronous workflows, and taking changes through testing and deployment. We welcome different technology backgrounds and value engineering fundamentals, ownership and learning ability.

What you will do

• Design, build and maintain backend services, APIs and business logic.
• Integrate internal applications, third-party platforms and enterprise systems through APIs, webhooks, messaging and background jobs.
• Build reusable connectors and adapters with authentication, data mapping, validation and error handling.
• Implement reliable workflows with timeouts, retries, idempotency, failure recovery and reconciliation.
• Work with databases, caching, application permissions and asynchronous processing.
• Understand existing codebases, trace dependencies and make reliable changes across services.
• Write automated tests, verify API contracts and troubleshoot failures across connected systems.
• Contribute to containerisation, CI/CD pipelines, AWS deployments and production monitoring.
• Use AI-assisted development tools to accelerate delivery while remaining accountable for correctness and quality.

Core requirements

• Backend programming: Strong skills in at least one language, such as Python, Java, TypeScript/JavaScript or Go, 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.
• Object-oriented programming: Good working understanding of abstraction, encapsulation, interfaces and composition, and 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.
• Security: Understanding of authentication, authorisation, tokens, service credentials and application permissions.
• 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.
• Ownership and judgment: Ability to navigate unfamiliar codebases, investigate issues across service boundaries, communicate clearly and make timely decisions.

Useful experience you do not need all of these

• Backend frameworks and runtimes: FastAPI, Django, Node.js or equivalents.
• Enterprise integrations: CRM, ERP, identity providers, billing, order management, inventory systems or other business platforms.
• 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 database migrations.
• AWS: ECS/Fargate, Lambda, API Gateway, S3, RDS, IAM, Secrets Manager and CloudWatch. Relevant Azure or GCP experience is also welcome.
• Containers and orchestration: Working understanding of Docker and Kubernetes, including containerising applications, configuration and deployment troubleshooting.
• Testing tools and practices: Familiarity with Robot Framework, Playwright and BDD scenarios written in Gherkin. Experience with API, integration and end-to-end testing across connected services.
• GitLab and CI/CD: Familiarity with GitLab 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.
• AI integrations: Model APIs, MCP servers/clients, agent frameworks and workflows.
• AI-assisted / agentic coding: Familiarity with coding assistants or coding agents for implementation, testing, debugging or exploring codebases is helpful, but not mandatory Candidates should be willing to learn these tools and critically review and validate generated code.

How we work

Our engineers own changes from understanding requirements through implementation, testing and deployment. You will work across existing services and larger codebases, break complex tasks into manageable changes, and use shared components and templates.

We use AI-assisted development tools to move faster. Engineers are expected to understand their changes, challenge generated suggestions and verify behaviour through meaningful tests and reviews. Prior experience with these coding tools is not a condition of selection.

Who will do well here

Engineers who enjoy connecting systems, understanding how they work and investigating what happens when they fail. You should be able to explain what you built, the decisions you made, how you handled failures and how you verified the result.

• Strong backend and integration engineering skills are the priority. Deep production experience in agentic AI or expertise in every listed technology is not required.