Why This Role Stands Out
This hybrid role offers an exciting opportunity to design and deploy cutting-edge Generative AI solutions, leveraging your expertise in LLMs and RAG architectures to build impactful applications. You'll thrive here if you're a skilled engineer eager to collaborate and contribute to innovative AI projects within a dynamic environment. Apply now to advance your career in this rapidly evolving field!
Quick Overview
Job Description
Job Title: SR GEN AI Engineer
Location: Minneapolis, MN
Duration: 12 Months + Extension
Bill Rate: $87/hour
Job Type: W-2 Contract
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD
POSITION OVERVIEW :
Job Description
Design, build, and deploy production-grade Generative AI solutions using Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and enterprise integrations.
Key Responsibilities
- Build end-to-end GenAI applications using LLMs (text, documents, QA, summarization, extraction)
- Implement RAG pipelines, data ingestion, chunking, embeddings, vector search, and grounded responses
- Develop APIs and microservices to integrate GenAI solutions with enterprise systems
- Implement structured outputs, function calling, and prompt frameworks
- Support evaluation, testing, monitoring, and continuous improvement of GenAI solutions
- Collaborate closely with the GenAI Architect and Agentic AI Engineers
Core Skills
- Hands-on experience with LLMs and RAG architectures
- Experience with vector databases and semantic search
- Practical understanding of prompt engineering and evaluation
2) Agentic AI Engineers (Autonomous AI Systems)
Role Purpose
Build Agentic AI systems that go beyond chatbots — autonomous, goal-driven AI agents that can reason, plan, call tools, and execute multi-step workflows.
Key Responsibilities
- Design and implement agentic AI workflows (planning, execution, observation, iteration)
- Build tool-using AI agents integrated with APIs, data sources, and enterprise systems
- Implement multi-agent or orchestrated agent architectures where required
- Combine Agentic AI with RAG for grounded, enterprise-safe responses
- Implement guardrails, safety checks, and evaluation mechanisms
- Debug, optimize, and operationalize agentic workflows in production
Core Skills
- Hands-on experience building agentic or multi-step AI workflows (not just prompting)
- Experience with orchestration frameworks and tool calling
- Understanding of AI safety, guardrails, and reliability patterns
- Ability to operationalize AI agents at enterprise scale
3) GenAI Architect — AI Coach (Architecture & Enablement)
Role Purpose
Act as the technical anchor and AI coach for the program — defining the GenAI architecture, standards, and guardrails, while guiding developers and ensuring long-term scalability.
Key Responsibilities
- Define the overall GenAI reference architecture (LLM, RAG, Agentic AI, data, security)
- Establish standards for prompt design, RAG patterns, evaluation, testing, and deployment
- Guide and mentor GenAI and Agentic AI engineers on design and implementation choices
- Drive architecture and design reviews; ensure reusability across regions and teams
- Define governance, guardrails, and responsible AI practices
- Act as the bridge between business stakeholders and technical teams
Core Skills
- Strong hands-on background in GenAI and enterprise architecture
- Deep understanding of LLM, RAG, Agentic AI, and deployment patterns
- Experience coaching teams through AI adoption and transformation
- Ability to translate business goals into technical solutions
Essential Skills
Top 3 Required Skills
- Experience in designing, building, and maintaining the data infrastructure that powers machine learning systems — pipelines, feature stores, data lakes, and real-time streaming architectures that feed model training and inference at scale.
- Led enterprise-wide architectural governance and helped create standards/frameworks driving efficiency.
- Strong experience in Databricks, Delta Lake, Apache Spark, Python, and Apache Airflow.
Top 3 Preferred Skills
- Any related certification
- Worked in the life and annuities industry
Education: At least a bachelor’s degree (or equivalent experience) in Computer Science, Software/Electronics Engineering, Information Systems, or a closely related field is required for the project
Equal Opportunity Employer: We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.
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