Senior Full Stack .NET Engineer

Technologies and Tools

Category - Technologies

Back end - C#, .NET (Core and current LTS), ASP.NET Core, Entity Framework Core

Data - MSSQL

APIs - REST, GraphQL

AI / Ecosystem - Claude Code (CLI and plugins), Anthropic APIs, MCP servers

Testing - xUnit or NUnit, automated integration and UI tests

Repository - GitHub

The Role and Why It Exists

As a Senior AI Practitioner (Full Stack .NET), you are a key delivery contributor who ships production-grade software at a high pace within the team's patterns, guardrails and standards.

You will own end-to-end slices of work across the stack: database, API, UI, tests and operation. You will use AI routinely to speed that work up while staying fully accountable for correctness, safety, quality and control.

AI-first delivery is our normal way of working. This role exists to deliver reliable full stack features quickly, and to help make that way of working repeatable for the rest of the team.

Key Accountabilities and Responsibilities

Technical Delivery

• Own delivery of features and technical slices end to end, from database and API to UI, including production support
• Design and build back-end services in C# and .NET on MSSQL, and front‑end features in Vue.js or React with TypeScript
• Integrate applications, data sources and third‑party systems through REST and GraphQL APIs
• Maintain and improve existing applications alongside new feature work
• Integrate external tools with AI interfaces where it helps delivery, such as MCP servers or Claude Code plugins
• Turn ambiguity into clarity by asking the right questions and aligning quickly on scope, constraints and acceptance criteria
• Provide accurate estimates and take part in architectural decisions with architects and principal engineers
• Break work into small increments, keep PRs tight and ship frequently
• Keep documentation current as part of delivery. Agents draft; you verify for correctness and usefulness

Collaboration and Culture

• Work with Product, QA and Operations to deliver outcomes, not just output
• Take an active part in code review as author and reviewer, giving clear and pragmatic feedback
• Mentor less experienced colleagues, in engineering practice and in effective use of AI tools
• Step up to unblock progress, improve reliability and strengthen the team's delivery system when needed

Qualifications

• 5+ years of commercial software development experience, with strong C# and .NET (Core and later) on the back end
• Solid experience building and consuming REST APIs; GraphQL experience is a plus
• Strong MSSQL skills: schema design, query writing and performance tuning
• Understanding of state management and of strategies for improving application performance on both sides of the stack
• Experience building and integrating front‑end and back‑end APIs in enterprise‑level production applications
• Experience with automated testing: unit, integration and automated UI tests
• Experience working to strong engineering standards: testing, CI/CD, code review and observability
• Able to explain the "why" behind technical tradeoffs and to see how a change connects to the broader system
• High AI workflow maturity: uses AI coding assistants such as Claude Code routinely on real‑world delivery, for first drafts of code, tests, SQL, docs and runbooks, while keeping full accountability for the result
• Good judgment on when to use AI (boilerplate, test generation, exploring APIs) and when to write code by hand (complex business rules, architectural decisions, security‑sensitive logic)
• Proven ability to write and refine prompts for implementation, architecture documentation and testing, using specificity, constraints, edge case coverage and expected output formats
• Able to analyze failure patterns to improve prompts step by step, and to document them (purpose, inputs, expected formats, limitations) for a shared team prompt library
• Experience setting strict guardrails when using AI to refactor complex code, so behavior is preserved, edge cases are handled and tests run before and after
• Delegates to agents with clear intent and constraints, iterates quickly, and verifies output rather than accepting it blindly: edge cases, failure modes, security, performance and operational behavior
• Contributes to team‑level leverage by improving templates, patterns, quality gates and delivery playbooks

Non-Technical

• Self‑driven member of a high‑performing team who cares about team culture and takes pride in the team’s results
• Collaborative, reliable and accountable; takes ownership and follows through
• Pragmatic and delivery‑focused; balances p