Please strictly adhere to the following resume naming convention:
Must Have TechnicalFunctional Skills
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, LangChain or LlamaIndex splitters).
Solid grasp of hybrid search (BM25 plus dense vectors, reciprocal rank fusion) and cross-encoder
reranking.
Has built agentic and multi-agent systems with LangGraph or a similar framework (CrewAI,
AutoGen, Semantic Kernel), and understands state, checkpointing, conditional routing and
interrupts. Has built LLM evaluation using golden datasets, retrieval metrics (recall@k, MRR), faithfulness and groundedness checks, and LLM-as-judge, with tools such as Ragas, DeepEval or Promptfoo. Can optimize cost and latency through model routing, prompt caching, context reduction and batching. Strong Python and FastAPI, plus working knowledge of Docker and CICD. Open-source stack and best practices Embeddings: open-source models such as bge, e5 or nomic, with the ability to benchmark them against commercial options. Knows how to avoid vendor lock-in, check licenses on models and libraries, pin versions, and keep components modular so they can be swapped. Cloud Preferred: Azure and Google Cloud Platform. For example, Azure OpenAI, Azure AI Search, Azure AI Document Intelligence, Vertex AI, Vertex AI Vector Search, GKE or AKS. Nice to have Healthcare domain experience (payer or provider), with knowledge of PHI and HIPAA requirements and familiarity with FHIR. Guardrails and security for LLM apps: PHI masking, prompt-injection defense, grounded answers with citations, audit logging. Fine-tuning experience (LoRA or QLoRA) on open-weight models.
Roles & Responsibilities
Were looking for a hands-on Applied AI Engineer who builds and ships AI products. Youll join a team
that finds AI opportunities across the business and turns them into working POCs and production
applications, including chatbots, document intelligence, and agent-driven workflows. Youll often run
3 4 projects at once and deliver real progress on each one every day. To do that, youll need to use AI
coding tools well.
Design, build and productionize RAG, agentic AI and multi-agent orchestrated applications, from
POC through deployment and support.
Own the full pipeline: ingestion and parsing, chunking, embeddings, indexing, hybrid retrieval,
reranking, generation, evaluation and monitoring.
Build multi-agent workflows with state management, tool calling, retries and human-in-the-
loop checkpoints.
Put evaluation frameworks and guardrails in place for accuracy, faithfulness, safety and cost.
Use Claude Code daily to move several independent projects forward in parallel.
Generic Managerial Skills, If any
Experience working in agile development projects and sprint deliver. A builder, not a strategist. Candidates should be able to show code they wrote, systems they shipped and production problems they fixed. The interview includes a live hands-on exercise using Claude Code.
Key Words to search in Resume
AI Engineer, cloud, LLM, python, scalable solution, Azure, Google Cloud Platform, Claude
Pre-Screening Questionnaire
7+ years in AI engineer
Designs, builds, and deploys production-grade artificial intelligence and machine learning applications to
solve practical business and engineering problems.
Role Descriptions: Applied AI engineer
Essential Skills: Applied AI engineer
Desirable Skills:
Keyword:
Skills: AI and Automation
Experience Required: 8-10
