Senior Back End Engineer

Elixirr Digital is transforming how consulting services are delivered. This role is critical to designing and implementing the backend infrastructure that powers our AI-driven solutions and internal agent platform. As a Senior Backend Engineer, you will leverage modern cloud services (AWS and Azure), open-source frameworks and the latest AI developer tooling to build a scalable, secure and opinionated platform for Elixirr’s next generation of tech-enabled consulting.

This is an engineering role for someone who wants to move fast in a modern AI-assisted software development lifecycle. You will not just use AI tools — you will help define how Elixirr’s engineering org adopts them responsibly: the harnesses, specs, evals, review practices and guardrails that turn AI-generated code into production-grade software.

At Elixirr Digital, you’ll have the opportunity to work with advanced tools, grow alongside a team of talented professionals, and make a lasting impact in diverse industries.

Candidates applying for employment contract kindly note this position is a onsite working opportunity from our locations in Cape Town or Johannesburg.

What you will be doing as a Senior Back End Engineer at Elixirr Digital?

Platform Architecture & Development

• Design, implement and maintain the core backend architecture for Elixirr’s AI-augmented consulting platform and agent platform.

• Drive decisions on microservices, containerization and serverless solutions (e.g., AWS Lambda, Azure Functions, ECS, AKS) based on performance, cost and scalability requirements.

• Own services end-to-end: architecture, implementation, testing, deployment, observability and on-call.

AI-Assisted Software Development Lifecycle

• Operate fluently across a modern, layered AI developer stack: editor-level copilots, agentic coding tools, repo-aware assistants, AI in CI (test generation, security and performance checks) and AI-assisted product discovery.

• Practice spec-driven, harness-based development: write precise specifications, acceptance criteria and context briefs that let AI tools generate useful code instead of guessing.

• Treat prompts, agents and evals as first-class engineering artifacts — versioned, reviewed and tested like any other code.

• Hold the quality bar high on AI-generated code: review rigorously for correctness, security, edge cases, performance and long-term maintainability. Volume comes from AI; quality comes from engineers.

• Build and maintain the internal guardrails — eval harnesses, security checks, policy controls — that make AI-assisted development safe and repeatable for the rest of the team.

• Help the team measure impact with clear engineering metrics (deployment frequency, cycle time, change failure rate, defect density) so we know where AI is actually helping.

Open-Source & Cloud Integration

• Evaluate and integrate open-source frameworks to reduce build time and improve reliability (e.g., FastAPI, Django, Spring Boot, Node.js frameworks).

• Leverage AWS and Azure services (e.g., EC2, S3, RDS, Cosmos DB, Event Hub, SQS, Event Bridge) to deliver high-availability, high-performance solutions.

• Integrate with the agent platform: LLM providers, vector stores, orchestration frameworks (Lang Graph, Semantic Kernel, Auto Gen) and retrieval pipelines.

Security & Compliance

• Implement robust security measures — OAuth 2.0, OIDC, JWT, fine-grained authorization, secrets management, data protection — by default, not as an afterthought.

• Address the specific risks of AI-assisted development: prompt injection, insecure AI-generated code, hallucinated dependencies, and supply chain risks from AI developer tooling.

• Ensure compliance with relevant industry regulations and Elixirr’s internal data governance standards (e.g., SOC 2, ISO 27001, GDPR).

Cross-Functional Collaboration

• Work closely with product, Dev Ops, front-end, AI engineers, data scientists and client-facing consultants to turn ambiguous problems into shipped product.

• Communicate architectural decisions and technical trade-offs clearly to both technical and non-technical stakeholders.

Performance, Reliability & Observability

• Set up and maintain logging, tracing, metrics and alerting — including…