THE OPPORTUNITY Over $20 trillion of freight moves through the U.S. economy each year-much of it still driven by fragmented data, manual processes, and domain-specific knowledge. For years, our client has operated at the intersection of data science and consulting-leveraging large-scale transportation data and advanced analytics to deliver high-value insights around logistics optimization, cost efficiency, and sustainability. These solutions have traditionally been delivered through a combination of data platforms, modeling, and human expertise. That model is now evolving. The organization has begun building an initial AI-driven prototype that combines its existing data assets, data science methodologies, and domain expertise into an agent-driven system capable of generating and delivering those insights directly. The early results have proven the concept-now the focus is on building a scalable, production-ready system on that foundation. This role represents one of the first major investments in that evolution. The individual in this position will play a key role in shaping how these systems are designed, scaled, and brought into production-directly influencing how the next generation of products in this space is built. ROLE DETAILS: As a Senior AI Engineer, you will design and build the intelligence layer behind these systems-defining how they reason, retrieve information, and operate reliably in production environments. You will design LLM-based architectures (RAG, agent orchestration, and evaluation frameworks) and bring them into production as scalable, reliable systems-where correctness and reliability directly impact real-world outcomes. This work spans the full lifecycle of AI systems-from structuring data and defining retrieval strategies, to shaping how models reason and make decisions, to ensuring outputs are accurate, grounded, and production-ready. Other notables: Employment Type : Direct Hire Compensation: Base : Base salary is flexible and will be determined based on experience and overall fit for the role. The estimated range is between $140k and $170k base. Bonus : This position is eligible for an annual performance bonus targeted at 15% of base salary, with the opportunity to earn up to 30% of base for exceptional company performance. Location/Travel : Client is based in Green Bay, Wisconsin, but this role can operate anywhere in the US. Preference for candidates in the Upper Midwest with openness to travel occasionally to client headquarters in Green Bay (expenses paid). Work Authorization : The client cannot sponsor visa candidates; therefore, work authorizations must be held by U.S. citizens, Permanent Residents (Green Card holders), or Visas not based on employer sponsorship (such as visas sponsored by a spouse or relative). Start Date : ASAP KEY SKILLS: Tier 1 – Core AI System Design (Non-Negotiable) AI System Design & Reasoning Ability to design how AI systems reason, not just consume APIs Retrieval-Augmented Generation (RAG) system design (chunking, retrieval, ranking, context assembly) Agentic architectures and workflow orchestration Orchestration patterns that scale AI systems from single workflows to platform-level capabilities LLM system design (RAG, retrieval strategies, embeddings) AI Architectural Judgment & Evaluation Frameworks Ability to make architectural tradeoffs (prompting vs fine-tuning, retrieval vs generation, latency vs accuracy) Evaluation frameworks for LLM systems (grounding, hallucination detection, offline/online validation) Strong Python Tier 2 – Data Driven AI Systems Experience evolving from traditional ML → modern GenAI systems Data modeling and data integration across multiple sources Complex SQL Experience designing data flows that support real-time or near-real-time AI decision-making Ability to structure and model data so AI systems produce accurate, context-aware, and grounded outputs Experience with ML frameworks (TensorFlow, PyTorch, etc.) (secondary now) Prompt engineering and response shaping strategies Tier 3 – Production & Infrastructure Cloud platforms (GCP preferred) Containerization (Docker, Kubernetes) Workflow orchestration (Airflow, etc.) Performance optimization (latency, cost, scaling of inference systems) Monitoring and observability for AI systems (latency, cost, output quality) Tier 4 – Supporting Engineering Skills React / Node General full-stack dev CI/CD, DevOps NICE TO HAVE REQUIREMENTS: Experience applying AI to complex, real-world domains with ambiguous or incomplete data Experience working with proprietary or messy operational datasets (non-clean, non-labeled environments) Experience building domain-specific AI systems Experience with entity resolution/knowledge graphs Familiarity with vector databases Experience designing AI evaluation or testing frameworks Exposure to agent frameworks (LangChain, LlamaIndex, etc.) JavaScript/TypeScript (if already covered via React/Node, not critical separately) Data modeling/data warehousing concepts Distributed data systems Application architecture knowledge (beyond practical experience) Data integration concepts (theoretical vs hands-on) RESPONSIBILITIES: AI System Design & Architecture Design and implement LLM-based systems, including RAG pipelines, agent workflows, and orchestration layers Define how AI systems reason through complex, domain-specific scenarios, ensuring outputs are accurate, grounded, and reliable Design how AI systems interact with users, ensuring outputs are interpretable, actionable, and aligned with real-world workflows Architect retrieval and context strategies (chunking, ranking, embeddings) that ensure AI outputs are based on correct and relevant information Contribute to defining platform-level AI patterns and architecture that scale across multiple products and use cases Data & Intelligence Layer Solve data integration and entity resolution challenges across fragmented and evolving data sources Design AI systems that operate effectively within real-world constraints, including latency, cost, and reliability requirements Production & System Reliability Build and maintain evaluation frameworks to validate AI system performance (e.g., grounding, hallucination mitigation, response quality) before production use Troubleshoot issues across model behavior, data pipelines, and system integration in production environments Develop and maintain testing strategies for both traditional software components and AI system behavior Build and maintain production-grade AI systems, ensuring scalability, performance, and operational stability Collaboration & Continuous Improvement Collaborate with product and business stakeholders to translate real-world problems into AI system designs and behaviors Continuously evaluate emerging AI technologies and incorporate them where they provide measurable improvements to system capability Mentor team members and contribute to best practices in AI system design, evaluation, and implementation NOTABLE BENEFITS: Competitive pay commensurate with experience Bonus (see above for details) Medical, Dental, Vision, Life insurance, AD&D, Disability, FSA (healthcare/childcare), HSA, 401k HOW TO APPLY: If you are a motivated and organized individual passionate about Information Technology, we would love to hear from you. To apply, please answer our applicant questions and submit your resume detailing your qualifications and relevant experience. We look forward to hearing from you! Amplified Sourcing is an equal opportunity employer and will consider all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws .
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