Requirement - Programming Engineer
Location- USA Remote
Contract W2
Assessment required
Key ResponsibilitiesAngular & 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.