AI/Claude Developer - LLM Platform

Technical Experience :

• Hands-on experience working with Claude (Anthropic APIs) or equivalent LLM platforms for code generation, automation, and developer workflows.

• Strong expertise in prompt engineering, prompt templating, and response optimisation.

• Experience designing and implementing Claude-based plugins, tools, and extensions, including API-based tool integrations, function calling, tool invocation patterns, and context-aware workflows for engineering tasks.

• Ability to design secure and governed LLM usage patterns including data masking, PII controls, and auditability.

• Experience building custom integrations and plugins for IDEs (e.g., IntelliJ, VS Code), CI/CD pipelines (GitLab, Jenkins), and developer portals or internal platforms.

• Strong backend development experience for plugin services using Java, Spring Boot, Node.js, or Python.

• Experience integrating AI into code review workflows, test generation pipelines, documentation automation, and ChatOps or DevOps assistants.

• Experience in improving developer productivity using AI-assisted tooling.

• Ability to automate code scaffolding, refactoring recommendations, test case generation (unit, integration, contract), and API documentation generation.

• Experience in building self-service developer tools and internal platforms.

• Strong expertise in building scalable microservices and REST APIs.

• Hands-on experience with cloud platforms (AWS preferred), containerisation (Docker), and Kubernetes-based deployments.

• Experience integrating AI services into event-driven architectures (Kafka preferred).

• Strong understanding of Git-based version control, GitLab CI/CD pipelines, and DevSecOps practices.

• Experience embedding AI into CI pipelines including auto code checks, review suggestions, build validation, and quality gates.

• Ability to drive test-first, quality-driven engineering culture.

Highly Valued Skills :

• Ability to act as an Individual Contributor Engineer (ICE) with end-to-end ownership.

• Strong analytical and troubleshooting skills for AI-integrated systems.

• Experience collaborating with cross-functional teams including DevOps, security, and platform teams.

• Excellent communication skills for AI adoption and developer enablement initiatives.

• Hands-on exposure to multiple AI coding assistants such as Claude, Copilot, and GitLab Duo.

• Experience with Retrieval-Augmented Generation (RAG), vector databases (e.g., Pinecone, OpenSearch), and LangChain or similar orchestration frameworks.