Software Developer Backend & AI

M.A.C. Solutions is a specialist provider of Industrial Data Communication, M2M solutions and Change Management solutions for the Process and Automation markets. M.A.C. Solution operates a software division (ProcessVue) offering applications to Alarm Management and IoT Analytics market. With offices in both UK and Europe, M.A.C. Solutions continues to grow nationally and internationally, offering customers the experience to Connect, Secure & Analyse their assets and data.

To keep up with demands from global growth, M.A.C. Solutions is looking to recruit a talented Backend & AI Software Developer who is passionate about software development, is willing to learn on the job and wants to work in a very diverse work environment.

Based in our software development centre in Chesterfield (hybrid/ remote), you will work on the AI and data side of our software as part of the development team, taking care of the following:

• Design and build secure, scalable backend services, APIs and integrations in C# / .NET
• Integrate LLMs (Anthropic, OpenAI or similar) into production features: prompts, structured outputs, context handling and error handling
• Control the cost, latency and reliability of AI features, including usage tracking, per-user limits and fallbacks
• Build retrieval and search using embeddings, vector search and RAG over customer data and documents
• Design agentic workflows (orchestration, memory, tool use) and build MCP servers and tools that give AI safe access to our data and systems
• Measure AI output quality with evaluation sets, user feedback scoring and regression checks
• Write and optimise SQL for large event and time-series datasets so dashboards and reports stay fast
• Build real-time features, background jobs, role-based access control and tamper-evident audit logging, with security built in (threat modelling, vulnerability scanning, awareness of the Cyber Resilience Act and AI Act)
• Analyse AI challenges, keep up with emerging AI approaches, and turn creative ideas into working proofs of concept
• Evaluate, fine-tune and deploy local / self-hosted LLMs
• Take part in code reviews and share backend and AI best practice with the team
• Follow QA procedures and processes defined in accordance with ISO 9001.

Engineering Foundation

• SignalR real-time communication experience
• Experience with .NET 10 / C# backend, APIs, async programming and scalable design
• SOLID principles, OOP and able to create clean code
• Experience with dependency injection, constructor injection, service lifetimes and implementing interface-based design
• Separation of concerns and layered architecture thinking
• Unit and integration testing (TDD principles, automated pipelines)
• Familiar with Entity Framework or Dapper or equivalent ORM
• PostgreSQL or Microsoft SQL Server experience.
• Know how to write efficient SQL including schema design and query optimisation
• 3rd party API integration
• Background job processing (Hangfire or equivalent)
• Agile / sprint-based delivery
• Nginx — web deployment and reverse proxy
• Monitoring, logging and troubleshooting of production services
• Experience building and deploying self-hosted / on-premises software
• Role-based access control, audit logging and secure-by-design practices
• Experience optimising queries and indexes on large time-series / event tables
• Experience handling real-time data streams and large datasets — ingestion, aggregation, caching and performance at scale

AI and LLM

• Experience developing using AI tools (Claude Code / GitHub Copilot)
• Hands-on experience connecting to OpenAI, Anthropic, or similar — prompting, context handling, structured outputs
• Working understanding of LLMs, RAG, embeddings, vector search, and semantic similarity
• Production experience shipping LLM-powered features (not only prototypes), including cost, latency, usage limits and fallbacks
• Experience designing retrieval pipelines over customer documents and data — chunking, embeddings, vector storage and semantic search
• Experience measuring AI output quality — evaluation sets, feedback scoring and regression testing
• Hands-on experience designing agentic workflows — orchestrator, memory, and tool-use patterns
• Experience fine-tuning or adapting models (e.g. LoRA / PEFT) and knowing when fine-tuning is better than prompting or RAG
• Experience running local / self-hosted LLMs (e.g. Ollama, vLLM, llama.cpp) for on-premises or air-gapped environments

Desirable

• React (Typ…