Data & GenAI Engineer (L3) (Hybrid In-Office)

Accuris•Denver, CO

5d•Hybrid

About The Position

Accuris transforms the world’s largest repository of standards and supply chain data into AI-driven insights and connected workflows – enabling engineers to work smarter, stay compliant, and innovate faster. As a Data & GenAI Engineer, you will help build the next generation of AI-powered products by combining strong data engineering fundamentals with modern agentic AI architectures. This role is focused on delivering production-ready GenAI solutions—not prototypes. You'll design retrieval-augmented generation (RAG) systems, build intelligent agents, develop reliable data pipelines, and help create AI experiences grounded in trusted engineering data. You'll work at the intersection of data, software engineering, and artificial intelligence, helping Accuris deliver scalable, measurable, and customer-facing AI capabilities that drive real business value.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent hands-on experience.
3–5 years of experience building software, data engineering solutions, or AI-enabled applications in a production environment.
Strong Python programming skills and experience writing clean, maintainable, and scalable code.
Strong SQL skills, including complex joins, aggregations, window functions, and data transformation techniques.
Understanding of modern data engineering concepts, including ETL/ELT pipelines, orchestration, incremental processing, data quality, and Medallion Architecture principles.
Working knowledge of large language models (LLMs), embeddings, vector databases, retrieval-augmented generation (RAG), and prompt engineering techniques.

Nice To Haves

Passion for emerging AI technologies and a desire to build practical, production-ready solutions using modern GenAI tools and frameworks.
Strong analytical and problem-solving skills with the ability to navigate ambiguity and solve complex technical challenges.
Ownership mindset with a focus on outcomes, continuous improvement, and delivering high-quality work.
Excellent communication and collaboration skills with the ability to work effectively across technical and non-technical teams.
Adaptability and curiosity, with the ability to learn quickly and evolve alongside rapidly changing AI technologies.

Responsibilities

Design, build, and support production-grade GenAI solutions, including retrieval-augmented generation (RAG), agentic workflows, document ingestion pipelines, and retrieval systems.
Develop and maintain scalable data pipelines that transform structured and unstructured information into high-quality datasets for AI and analytics applications.
Implement prompt engineering, retrieval strategies, vector search capabilities, and grounding techniques to improve model performance, accuracy, and reliability.
Build and support agent orchestration frameworks, including supervisor-agent patterns, task delegation, workflow coordination, and multi-step reasoning processes.
Establish best practices for testing, observability, evaluation, monitoring, and documentation to ensure AI and data solutions are measurable and production-ready.
Collaborate with product, engineering, and data teams to deliver innovative AI-powered features that improve customer outcomes and accelerate product innovation.