ROLE OVERVIEW :

Full Stack Engineers with AI skills to design, develop and deploy full-stack applications applying Claude AI and GenAI tools to accelerate engineering workflows across the entire SDLC from requirements and design through to deployment and monitoring.

KEY RESPONSIBILITIES :

- Design and deliver end-to-end web applications (UI through API through database) integrating AI features.

- Build scalable, production-grade RESTful APIs using Python/FastAPI or Node.js.

- Develop responsive, high-performance front-end applications using Angular 16+ or equivalent modern frameworks.

- Integrate AI/ML capabilities OpenAI, Azure AI, Claude (Anthropic), AWS AI via APIs into product features.

- Use Claude AI to accelerate SDLC tasks : code generation, code review, debugging, refactoring, and technical documentation.

- Apply prompt engineering techniques to craft effective prompts that boost development productivity and quality.

- Work closely with AI Architects, QEs, and BAs within Agile squads to deliver sprint commitments.

- Write clean, secure, testable code aligned with architectural standards and coding guidelines.

- Participate in code reviews, design discussions, and Agile ceremonies.

- Support cross-platform optimisation, performance tuning, and scalability improvements.

- Integrate asynchronous messaging and event-driven architectures (Kafka, RabbitMQ) where required.

- Deploy and manage applications using Docker and Kubernetes.

TECHNICAL SKILLS :

- Full-stack development experience of 3-5 years for proficient and 6-8 years of experience for specialist.

- Backend : Python / FastAPI or Node.js clean API design, versioning, auth, error handling, observability.

- Frontend : Angular 16+ (preferred) or equivalent modern framework responsive, high-performance UIs.

- Databases : SQL and NoSQL schema design, indexing, query optimisation.

- APIs : RESTful design patterns; experience with WebSockets or real-time communication preferred.

- Infrastructure : Docker, Kubernetes deployment, scaling, container orchestration.

- Messaging : Kafka, RabbitMQ, or similar asynchronous processing systems.

- Proficient in using Claude AI (Anthropic) Claude Sonnet / Haiku for day-to-day engineering tasks.

- Prompt engineering : ability to craft, iterate, and optimise prompts for code generation, explanation, review, and test creation.

- AI integration : experience calling LLM APIs (Claude, OpenAI, Azure OpenAI, AWS Bedrock) from application code.

- Understanding of LLM concepts : context windows, token limits, embeddings, RAG basics, latency and cost trade-offs.

- Use of AI tools (Claude, GitHub Copilot, or equivalent) to measurably reduce development cycle time.

- Collaborative development with data scientists / ML engineers to productionise AI components.