Q
Applied AI engineer
Q1 Technologies
9 hours ago
Full-time
On-site
Aurora, Illinois, United States
Job Description: Please strictly adhere to the following resume naming convention:
ALL CAPS, NO SPACES B/T UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
i.e. PTN_US_9999999_SKIPJOHNSON0413
MSP Owner: William Bristol Location: See Below Duration: 6 months
Must Have Technical/Functional 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 CI/CD. 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 GCP. 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
We're looking for a hands-on Applied AI Engineer who builds and ships AI products. You'll 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. You'll often run
3-4 projects at once and deliver real progress on each one every day. To do that, you'll 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, GCP, 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 Comments for Suppliers: 4 Positions open
ALL CAPS, NO SPACES B/T UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
i.e. PTN_US_9999999_SKIPJOHNSON0413
MSP Owner: William Bristol Location: See Below Duration: 6 months
Must Have Technical/Functional 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 CI/CD. 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 GCP. 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
We're looking for a hands-on Applied AI Engineer who builds and ships AI products. You'll 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. You'll often run
3-4 projects at once and deliver real progress on each one every day. To do that, you'll 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, GCP, 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 Comments for Suppliers: 4 Positions open