Lead AI & Data Scientist

About the role

The Lead AI & Data Scientist will help define, implement, and operationalize Trustwell’s artificial intelligence strategy across products, engineering, data, and internal operations. This role is responsible for turning our existing and new AI systems into reliable, governed, measurable, and reusable capabilities that create practical business value.

Responsibilities

• Define and help execute Trustwell’s applied AI strategy across product, engineering, data, and internal business operations
• Lead the implementation of AI capabilities that are practical, measurable, secure, and aligned to business outcomes
• Establish AI governance practices, including usage policies, risk controls, evaluation standards, approval processes, and ongoing monitoring
• Partner with Engineering to design repeatable AI implementation patterns for LLMs, agents, retrieval-augmented generation, structured outputs, model evaluation, observability, and production operations
• Partner with Product to identify, evaluate, and prioritize AI-enabled product opportunities that improve customer value and operational efficiency
• Develop frameworks for assessing AI use cases, including feasibility, risk, data availability, implementation complexity, cost, and expected business impact
• Create and maintain standards for responsible AI usage, including data handling, prompt management, model selection, explainability, auditability, and human-in-the-loop controls
• Build and guide AI evaluation processes, including test datasets, regression testing, hallucination detection, quality scoring, accuracy measurement, and production feedback loops
• Help establish internal AI adoption processes, including development workflows, engineering enablement, training, approved tooling, and practical usage guidelines
• Work with Security, Legal, Compliance, and IT stakeholders to ensure AI implementations align with Trustwell’s data protection, privacy, contractual, and security obligations
• Analyze structured and unstructured data to identify opportunities for automation, prediction, classification, summarization, enrichment, and decision support
• Develop prototypes, proofs of concept, and production-ready analytical or AI workflows where appropriate
• Provide technical leadership on model selection, vendor evaluation, build-versus-buy decisions, AI cost management, and long-term platform strategy
• Collaborate with data engineering and application teams to improve data readiness, data quality, metadata, lineage, and retrieval strategies for AI-enabled systems
• Define metrics and reporting to measure AI adoption, performance, quality, cost, risk, and business impact
• Act as a trusted advisor and mentor to engineering, product, and business teams as they adopt AI responsibly and effectively

Requirements

• 8+ years of professional experience across data science, machine learning, AI engineering, data engineering, software engineering, or related technical disciplines, with demonstrated experience leading applied AI initiatives from concept through implementation
• Direct experience establishing or operating AI governance, evaluation, adoption, or production-readiness processes within an organization
• Hands-on experience implementing AI or machine learning capabilities in a production, enterprise, or customer-facing environment
• Strong understanding of modern AI technologies, including LLMs, embeddings, retrieval-augmented generation, prompt engineering, structured outputs, agentic workflows, and model evaluation
• Experience translating business problems into practical AI, data science, analytics, or automation solutions
• Ability to evaluate AI use cases based on business value, technical feasibility, data readiness, operational risk, and implementation cost
• Experience establishing responsible AI practices, including data privacy, security, bias awareness, explainability, human review, auditability, and acceptable use controls
• Strong analytical skills with the ability to work with structured and unstructured data
• Experience with Python and common data science, machine learning, or AI development libraries and frameworks
• Familiarity with APIs, cloud services, data pipelines, vector stores, and production software delivery practices
• Experience defining quality measurement approaches for AI systems, including benchmark datasets, test cases, quality scoring, drift monitoring, and regression evaluation
• Strong communication skills with the ability to explain AI concepts, risks, trade-offs, and implementation plans to technical and non-technical stakeholders
• Pragmatic judgment with the ability to balance innovation, governance, speed, cost, and risk
• Collaborative, approachable working style with the ability to influence across teams without direct authority

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related field, or equivalent professional experience
• Advanced degree in a quantitative, technical, or AI-related discipline preferred but not required
• Experience implementing generative AI or LLM-based capabilities in a SaaS, software, regulatory, compliance, supply chain, or data-intensive business environment
• Experience with AI governance frameworks, model risk management, responsible AI programs, or enterprise AI operating models
• Experience with OpenAI, Anthropic, Google, AWS, Azure, or similar AI/ML platforms
• Experience with vector databases or retrieval systems such as Chroma, Pinecone, Weaviate, OpenSearch, MongoDB Atlas Vector Search, or similar technologies
• Experience with data platforms such as MongoDB, Snowflake, SQL Server, PostgreSQL, or cloud-native data services
• Experience with cloud environments, preferably AWS
• Experience with MLOps, LLMOps, observability, evaluation pipelines, model monitoring, and AI cost management
• Experience working with product and engineering teams to move AI prototypes into production
• Experience creating internal AI usage policies, review boards, enablement materials, training programs, or implementation playbooks
• Experience with compliance-sensitive environments involving customer data, privacy requirements, auditability, or regulated industries

Benefits

• Full healthcare benefits, including medical, dental, and vision
• Supplemental benefits, including STD, LTD, HSA, 401k, etc.
• Responsible Time Off (PTO) + Holiday Pay
• Competitive Compensation + Bonus!
• Excellent culture, growth opportunities, plus much more...

Pay

The pay range for this role is: 150,000 - 170,000 USD per year (Remote (United States))

Schedule

Remote (United States)