Technical Lead - Data Science & AI

Your Job

Koch Capabilities is seeking a Technical Lead - Data Science & AI to provide technical leadership for enterprise-scale Data Science, Machine Learning, and Generative AI initiatives. This role will be responsible for shaping AI architecture, defining engineering standards, guiding implementation teams, and delivering scalable AI-powered products that create measurable business value. You will play a critical role in advancing our AI capabilities by partnering with business and technology leaders to transform opportunities into practical, secure, and responsible AI solutions.

Our Team

You will join a team focused on accelerating AI adoption across the enterprise through advanced analytics, machine learning, and Generative AI capabilities. Working closely with business stakeholders, data scientists, AI engineers, software engineers, and platform teams, you will help define the future of enterprise AI solutions while fostering innovation, engineering excellence, and responsible AI practices.

What You Will Do

• Define and drive the enterprise Data Science and Generative AI roadmap aligned with strategic business objectives.
• Architect end-to-end AI, machine learning, and GenAI solutions spanning data ingestion, feature engineering, model development, deployment, monitoring, and governance.
• Design and implement advanced GenAI applications utilizing Retrieval-Augmented Generation (RAG), AI agents, prompt orchestration, vector databases, and enterprise knowledge systems.
• Establish reusable AI architecture patterns, engineering standards, and best practices to enable scalable solution delivery.
• Provide technical leadership and mentorship to Data Scientists, AI Engineers, Data Engineers, and Software Engineers.
• Lead architecture reviews and guide the adoption of emerging AI technologies and platforms.
• Design and evolve scalable AI platforms leveraging Snowflake, AWS, and modern cloud-native architectures.
• Implement MLOps and LLMOps capabilities including CI/CD pipelines, model lifecycle management, observability, monitoring, and evaluation frameworks.
• Define architecture guardrails for data privacy, security, compliance, responsible AI, explainability, and risk management.
• Partner with business leaders and stakeholders to translate complex business challenges into innovative AI-powered solutions.
• Present AI strategies, architecture decisions, roadmaps, and business outcomes to technical and executive audiences.
• Drive the successful execution of key initiatives including Claria Orchestrator Rewrite and new feature development aligned with the product roadmap.

Who You Are (Basic Qualifications)

• 8+ years of experience designing, architecting, and delivering enterprise-scale Data Science, Machine Learning, and Generative AI solutions.
• Experience developing and implementing solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, AI agents, and enterprise AI applications.
• Experience designing cloud-based data and AI platforms utilizing Snowflake, AWS, or comparable technologies.
• Experience implementing MLOps and/or LLMOps practices, including model deployment, monitoring, observability, and lifecycle management.
• Experience leading cross-functional engineering teams and providing technical guidance across AI, machine learning, data engineering, and software development domains.
• Experience designing architecture frameworks that address data governance, security, privacy, compliance, and responsible AI requirements.
• Strong proficiency in Python and SQL for analytics, model development, or AI solution delivery.
• Experience partnering with business stakeholders to define AI strategies, architecture roadmaps, and solution outcomes.

What Will Put You Ahead

• Experience with enterprise AI platforms including OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or equivalent LLM technologies.
• Experience building multi-agent systems using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
• Experience implementing enterprise search and knowledge retrieval solutions using Azure AI Search, Elasticsearch, OpenSearch, or Microsoft Graph APIs.
• Experience with vector database technologies including Pinecone, Weaviate, ChromaDB, Qdrant, Milvus, or Snowflake Cortex Search.
• Experience developing machine learning models using Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Experience with modern data engineering technologies such as Spark, PySpark, Kafka, Airflow, dbt, AWS Glue, or similar platforms.
• Experience with containerization, Kubernetes, Infrastructure as Code, and DevOps automation practices.
• Experience participating in enterprise architecture review boards and driving organization-wide technology standards.
• Demonstrated success influencing business leaders, presenting to executive audiences, and delivering measurable value from AI investments.
• Experience defining AI governance frameworks, model evaluation strategies, and responsible AI practices within large organizations.

At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy.

Who We Are

At Koch, employees are empowered to do what they do best to make life better. Learn how ourxa0xa0helps employees unleash their potential while creating value for themselves and the company.

Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results.