Applied AI engineer

Claude Code and AI-assisted development

Strong day-to-day experience with Claude Code, including a disciplined workflow: plan before coding, use CLAUDE.md project memory, implement in small steps with tests, and review the code

it generates.

Has run parallel workstreams using git worktrees, multiple sessions, subagents with focused roles (such as tester, reviewer or refactorer), custom slash commands, hooks and MCP integrations.

Can deliver deployable progress on several projects in the same day without sitting idle while a model generates.

Applied AI engineering

Has built and taken to production RAG systems, with hands-on use of parsing and chunking libraries (for example Unstructured, Docling, LanEligible to workhain or LlamaIndex splitters).

Solid grasp of hybrid search (BM25 plus dense vectors, reciprocal rank fusion) and cross-encoder reranking.