Programming Engineer

Position :: Programming Engineer - LS

*Assessment required based on Angular, SQL, Entity Framework, Open AI API*

Job Description:

Key Responsibilities

Angular & Front-End Engineering

Architect, build, and maintain scalable Angular applications using modern patterns: standalone components, signals, lazy loading, and module federation.
Lead front-end technical design - component libraries, state management routing, and performance budgets.
Build accessible (WCAG 2.1 AA), responsive interfaces that work consistently across browsers and devices.
Define and uphold front-end coding standards; conduct thorough, constructive code reviews.
Integrate Angular apps with RESTful and GraphQL APIs, applying robust error handling, retry logic, and security best practices (OAuth 2.0 / OIDC).
Mentor and support junior and mid-level developers through pairing, design reviews, and knowledge sharing.

SQL & Data Access

Write performant T-SQL queries, stored procedures, views, and functions against SQL Server (2019/2025), PostgreSQL
Contribute to database schema design and data modelling in collaboration with DBAs and back-end engineers.
Analyse query execution plans and apply indexing strategies to resolve performance bottlenecks.
Utilise SQL Server 2025's native VECTOR data type for AI-powered semantic search and retrieval-augmented generation (RAG) pipelines.
Implement data access layers using Entity Framework Core, Dapper, or similar ORMs - choosing the right tool for the job.
Participate in database migration planning, code-first migrations, and version-controlled schema management.

DevOps Exposure & Engineering Culture

Work confidently within CI/CD pipelines (GitHub Actions) - understanding build, test, and deployment stages.
Containerise and run applications using Docker; understand Kubernetes concepts for deployment in AKS or similar environments.
Manage environment configurations securely using secrets management tools (environment variables, .env conventions).
Engage with infrastructure-as-code practices (Terraform, Bicep) at a working level - able to read, adjust, and contribute to IaC scripts.
Participate in monitoring and observability: dashboards, alerts, and log analysis using Application Insights, or Grafana.
Contribute to incident response, post-mortems, and continuous improvement of deployment reliability.

AI in Day-to-Day Development

Actively use AI coding assistants (GitHub Copilot, Cursor, Claude) to accelerate feature development, generate boilerplate, and explore solutions faster.
Apply prompt engineering skills to get the most from LLMs - writing precise prompts for code generation, test writing, documentation, and debugging.
Build AI-integrated features chatbots, semantic search, content generation, or recommendation engines using APIs such as OpenAI, Azure OpenAI, or Anthropic.
Implement Retrieval-Augmented Generation (RAG) patterns combining vector databases or SQL Server VECTOR columns with LLM inference.
Evaluate AI-generated code critically: spot errors, security issues, and architectural mismatches before they reach production.
Stay current with the fast-moving AI tooling landscape and share learnings with the team - blog posts, demos, lunch-and-learns.

Required Qualifications

Experience: 7+ years of professional software engineering experience.
Angular: 5+ years building production Angular applications (v12 or later); strong TypeScript and RxJS fundamentals.
SQL: 3+ years writing and optimising SQL in SQL Server, PostgreSQL.
DevOps: Familiarity with CI/CD pipelines, Docker, and cloud deployment workflows in AWS or equivalent Cloud.
AI Tooling: Hands-on experience using AI coding tools (Copilot, Claude, or equivalent) in real projects.
AI Integration: Experience consuming LLM APIs (OpenAI, Anthropic) in a front-end or full-stack context.
APIs & Security: Solid understanding of REST and GraphQL API design, authentication patterns, and security principles.
Agile: Experience working in Agile / Scrum teams with Jira, Azure Boards, or equivalent.
Communication: Clear, confident communicator - comfortable explaining technical trade-offs to non-technical stakeholders.