What will you be doing?
- Design and implement AI agents facilitating the full development cycle of optimization applications with a focus on leveraging Gurobi optimization expertise and best practices.
- Architect and maintain the integration of optimization components, including Gurobi's solver and related libraries, into AI features of existing and new products.
- Partner with cross-functional teams (AI Innovation Lab, Optimizer team, Experts, Product Management, Marketing) to align on AI feature requirements, gather domain knowledge, and ensure best practices are reflected across AI systems and products.
- Develop and refine prompt and context engineering strategies for production AI systems.
- Participate in the quality testing of AI features by designing test cases and evaluations.
- Troubleshoot AI feature quality and performance issues. Be an escalation contact for service incidents related to AI features to help our support team when necessary.
- Serve as an internal AI subject matter expert, evaluating use cases across teams and providing technical guidance and recommendations on AI applicability and approach.
- Collaborate with a team of software developers and QA engineers of the Platform team following our agile methodology. The role involves a substantial amount of teamwork and individual contribution.
What experience and qualifications should you have?
- 5+ years of experience as a software engineer.
- 2+ years of hands-on experience with prompt engineering, knowledge base management, or machine learning application development.
- 2+ years of hands-on experience developing mathematical optimization applications.
- Bachelor’s in Computer Science or related technical field or equivalent professional experience.
- Fluent in English.
What skills, abilities, and behaviors should you have?
- Proficient with at least one programming language such as Python, Node.js or Go.
- Good understanding of generative AI agents including prompt and context engineering, orchestration, vector databases, and RAG architecture.
- Prior experience with one or more AI platforms (Anthropic, AWS Bedrock, OpenAI, Agentforce), AI protocols (MCP, A2A), and AI orchestration frameworks (LangChain, LangGraph, Strands or custom).
- Solid understanding of machine learning concepts and applications, including reinforcement learning techniques.
- Strong understanding of mathematical optimization concepts and experience modeling or solving optimization problems.
What other requirements should you have?
- Awareness of responsible AI practices, including output safety, guardrails, and AI governance, with familiarity with the OWASP Top 10 for LLMs would be beneficial.
- Prior experience with CI/CD pipelines development would be advantageous.
- Prior experience with ML frameworks (MetaFlow, MLFlow, DVC, Kuberflow, LakeFS) would be advantageous.
- Good understanding of container technology (Docker) would be beneficial.
- Prior engagement with agile methodologies, such as Scrum, would be advantageous.
Your Alignment with our Gurobi Core Values:
- Customer Focus: Verbal & written communication skills that bring clarity and build trust.
- Power of the Team: Motivated with a team-oriented mindset that aims to both inspire and be inspired by others.
- Innovation: The courage to bring ideas forward and see yourself as an integral part of our global team.
- Dedication: Organized and agile, focusing on meeting professional objectives while promoting a healthy work/life balance.
- Integrity: Promise to uphold honesty as your compass and conduct all business practices with an ethical mindset and fiscal responsibility.
Top Skills
What We Do
Gurobi produces the world’s fastest and most powerful mathematical optimization solver – the Gurobi Optimizer – which is used by leading global companies across more than 40 different industries to rapidly solve their complex, real-world problems and make automated decisions that optimize their efficiency and profitability. As the market leader in mathematical optimization software, we aim to deliver not only the best solver, but also the best support – so that companies can fully leverage the power of mathematical optimization (on its own or in combination with other AI techniques such as machine learning) to drive optimal business decisions and outcomes.






