Overview As an AI leader, you will design and deploy agentic AI systems and enterprise ML solutions that translate data into trusted business insights. You will collaborate with cross-functional teams to frame high-value problems and build scalable, governance-aware AI that supports decision-making at scale. Your work will span from data integration and model development to evaluation, risk, and explainability, with a focus on real business impact. Join a mission-driven culture that values collaboration and measurable outcomes.
Responsibilities- Design and build advanced ML models integrating structured and unstructured data to drive business decisions
- Create enterprise knowledge systems enabling AI agents to retrieve, reason over, and operationalize knowledge
- Partner with stakeholders to identify and prioritize problems solvable with Agentic AI, LLMs, and ML
- Develop business-centric evaluation frameworks covering coverage, relevance, trust, explainability, and adoption
- Architect agentic AI systems that reason, plan, and act across tools, workflows, and data sources
- Design multi-agent and tool-augmented LLM solutions for multi-step processes
- Collaborate with engineering to deploy scalable, secure, and high-performance AI solutions
- Implement monitoring, guardrails, and risk controls for LLM and agentic systems
- Mentor peers on applied AI and business-driven problem solving
Key requirements- Agentic AI design experience with systems that can reason, plan, and act across multiple platforms
- Hands-on Enterprise LLM applications (RAG, tool use, orchestration, evaluation)
- Strong NLP experience with unstructured text and language-driven workflows
- Hands-on ML experience with gradient boosting methods and model interpretability options
- MS in Computer Science, Machine Learning, Data Science, or related quantitative field
- 3+ years delivering AI/ML in production environments
- 5+ years of Python experience; distributed data processing experience is a plus
- Strong ability to solve business problems using AI and explain complex concepts to diverse audiences
- Experience working in cross-functional, enterprise environments
- Excellent communication with technical and non-technical audiences
- Cross-functional collaboration
- Mentorship and leadership within teams
- Agentic AI design
- Large Language Models (LLMs) - enterprise applications
- NLP and unstructured data processing
