K
Staff AI Engineer
KPG99 INC
3 hours ago
Full-time
On-site
Milwaukee, Wisconsin, United States
Staff AI Engineer
Location: Milwaukee, WI / Raleigh, NC – Hybrid
Contract: 1+ Year
Work Authorization: USC Only
Considering making an application for this job Check all the details in this job description, and then click on Apply.
Required Qualifications Proven experience
personally building and deploying AI systems into production from scratch . Strong hands-on experience with
LLMs, Generative AI, RAG, embeddings, AI agents, and modern AI application architectures . Experience with model selection, model APIs, prompt engineering, retrieval strategies, agentic workflows, and AI system integration. Strong experience with
Python and SQL .
Technical Environment The team works across a broad modern technology stack, including: Python, SQL, PostgreSQL, React, C#, iOS, LLMs, Generative AI, Agentic AI, RAG, Embeddings, Model APIs, Cloud Platforms, AI Evaluation, Observability, and Production AI Systems. Candidates are
not expected to have experience with every technology listed . Strong software engineering fundamentals, deep AI application experience, architecture ownership, and demonstrated production experience are more important than knowledge of every individual technology. Staff-Level Expectations At the Staff level, the successful candidate will be expected to: Own architecture across a product or technical domain. Make high-impact technical decisions and communicate tradeoffs effectively. Establish reusable AI engineering patterns that can be adopted by other teams. Raise the technical quality and judgment of the broader engineering organization. Balance hands-on implementation with technical leadership and mentorship. Take ownership from
problem discovery through architecture, implementation, production deployment, evaluation, and iteration . Location & Work Arrangement Milwaukee, WI:
Preferred location, with approximately 2–3 days/week onsite. Raleigh, NC:
Hybrid candidates considered. Chicagoland:
Candidates who can travel to Milwaukee approximately 2 days/week may also be considered. Hybrid requirements are flexible for an exceptionally strong candidate with the required AI and architecture background. Interview Process Approximately
3 rounds , beginning with two back-to-back
30-minute technical discussions , followed by a potential final round. The interview process will focus on: AI system architecture Production AI engineering LLM/RAG/agentic AI experience Software engineering fundamentals Technical decision-making and tradeoffs Customer/product judgment Architecture ownership and technical leadership Important Candidate Requirement Candidates must demonstrate
real, hands-on ownership of production AI systems . xsgimln Experience limited primarily to AI integrations, experimentation, demonstrations, or POCs will not be sufficient for this Staff-level position.
Considering making an application for this job Check all the details in this job description, and then click on Apply.
Required Qualifications Proven experience
personally building and deploying AI systems into production from scratch . Strong hands-on experience with
LLMs, Generative AI, RAG, embeddings, AI agents, and modern AI application architectures . Experience with model selection, model APIs, prompt engineering, retrieval strategies, agentic workflows, and AI system integration. Strong experience with
Python and SQL .
Technical Environment The team works across a broad modern technology stack, including: Python, SQL, PostgreSQL, React, C#, iOS, LLMs, Generative AI, Agentic AI, RAG, Embeddings, Model APIs, Cloud Platforms, AI Evaluation, Observability, and Production AI Systems. Candidates are
not expected to have experience with every technology listed . Strong software engineering fundamentals, deep AI application experience, architecture ownership, and demonstrated production experience are more important than knowledge of every individual technology. Staff-Level Expectations At the Staff level, the successful candidate will be expected to: Own architecture across a product or technical domain. Make high-impact technical decisions and communicate tradeoffs effectively. Establish reusable AI engineering patterns that can be adopted by other teams. Raise the technical quality and judgment of the broader engineering organization. Balance hands-on implementation with technical leadership and mentorship. Take ownership from
problem discovery through architecture, implementation, production deployment, evaluation, and iteration . Location & Work Arrangement Milwaukee, WI:
Preferred location, with approximately 2–3 days/week onsite. Raleigh, NC:
Hybrid candidates considered. Chicagoland:
Candidates who can travel to Milwaukee approximately 2 days/week may also be considered. Hybrid requirements are flexible for an exceptionally strong candidate with the required AI and architecture background. Interview Process Approximately
3 rounds , beginning with two back-to-back
30-minute technical discussions , followed by a potential final round. The interview process will focus on: AI system architecture Production AI engineering LLM/RAG/agentic AI experience Software engineering fundamentals Technical decision-making and tradeoffs Customer/product judgment Architecture ownership and technical leadership Important Candidate Requirement Candidates must demonstrate
real, hands-on ownership of production AI systems . xsgimln Experience limited primarily to AI integrations, experimentation, demonstrations, or POCs will not be sufficient for this Staff-level position.