Empowering responsible AI innovation at the speed of progress We are seeking a transformational engineering leader to build and scale our AI Safety Services organization. This role will be at the forefront of shaping how enterprises deploy advanced AI models safely, responsibly, and with confidence—without slowing innovation. The Impact You Will Drive Accelerate responsible AI adoption by delivering world-class safety services that enable customers to launch next-generation models and applications at scale. Influence industry standards by establishing best-in-class methodologies, tools, and benchmarks that define how safe AI systems are built and evaluated. Supercharge customer outcomes through seamless platforms and workflows that balance speed, trust, and model accountability. What You'll Lead & Deliver People & Leadership Build, coach, and inspire a high-performing team of AI engineers, platform engineers, and product leaders Foster a culture grounded in impact, innovation, security, and rapid learning Establish agile practices that drive velocity without compromising safety or quality Customer & Product Partnership Work directly with enterprise customers to deeply understand use cases, risks, and innovation priorities Translate customer insight into technical roadmaps aligned with fast-paced AI adoption cycles Advocate for customer-centric engineering and measurable business value AI Safety Platforms & Capabilities Oversee delivery of platforms for model alignment evaluation, adversarial testing, drift detection, and interpretability Drive architecture decisions, including build-vs-buy strategies, tool integrations, and ecosystem collaboration Define and enforce engineering best practices—secure coding, observability, IaC, automation, SLAs/SLOs Innovation & Thought Leadership Stay ahead of cutting-edge AI safety research, regulatory evolution, and adversarial trends Pilot emerging techniques and frameworks that enhance model reliability, security, and trust Build IP and reusable assets that scale customer adoption and platform maturity What You Bring 15+ years in software engineering with 10+ years leading high-impact technical teams or programs Proven experience delivering AI/ML or large-scale data platforms (MLOps, model eval systems, AI safety tooling a plus) Strong leadership track record in talent development, mentoring, and high-trust culture building Ability to translate deep technical concepts into business impact and customer value Technical Expertise Hands-on experience with Python, TensorFlow/PyTorch, containerization (Docker, Kubernetes), APIs, and data systems (SQL/NoSQL) Experience operating in cloud environments (AWS, Azure, GCP) Familiarity with LLMs, prompt evaluation, adversarial testing, and model interpretability Bonus: LangChain/LangGraph, distributed systems (Spark/Flink), SOC2/ISO27001, AI governance frameworks
Build the data foundation powering AI, automation, and enterprise intelligence We are seeking a hands-on Vice President of Data Engineering & Architecture to lead the strategy, design, and execution of our enterprise data ecosystem. This leader will define how data is structured, stored, governed, and leveraged to drive analytics, automation, and AI initiatives across the organization. The ideal candidate brings deep expertise in architecting large-scale data warehouses and data lakes, with a strong command of OLAP and OLTP principles, and a passion for building modern, intelligent data platforms. Key Responsibilities Strategic Data Architecture Design and implement scalable, high-performance enterprise data architectures — including data warehouses (AWS Redshift, SQL Server) and structured/unstructured data lakes. Develop forward-looking architectural blueprints that seamlessly support analytics, operational systems, and AI workloads. End-to-End Data Engineering Lead the design, build, and maintenance of robust data pipelines and enterprise integration frameworks. Ensure data is accurate, consistent, discoverable, and accessible across all business domains. Performance Engineering Apply deep OLTP and OLAP expertise to optimize database design, query performance, and workload throughput. Drive continuous improvement in data platform efficiency, scalability, and resilience. Cross-Functional Collaboration Work closely with automation, AI, analytics, and software engineering teams to align data strategy with business outcomes. Integrate data systems into intelligent workflows powering automation and AI adoption. Data Modeling & AI Enablement Architect scalable semantic and analytical data models optimized for natural-language querying and AI-driven analytics. Enable clean, well-structured data for business intelligence platforms (Power BI and others). Governance & Data Quality Establish enterprise data governance, metadata management, and data quality standards. Operationalize master data management, ensuring consistency, compliance, and trusted enterprise data assets. Leadership & Talent Development Build, mentor, and scale a high-performing team of data engineers and architects. Foster a culture centered on innovation, reliability, automation, and excellence. Qualifications Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field. 14+ years of progressive experience in data engineering or data architecture within enterprise environments. Proven ability to architect and deliver large-scale data warehouses and data lakes using AWS Redshift and/or SQL Server . Deep understanding of OLAP/OLTP systems , data modeling, and performance optimization. Advanced proficiency in SQL and enterprise data integration practices (ETL/ELT, APIs, streaming pipelines). Hands-on experience with Power BI or similar enterprise BI platforms. Exposure to AI/ML data preparation, semantic modeling, and natural-language query enablement preferred. Strong communication and stakeholder-management skills; ability to influence technical and business leaders. Demonstrated track record partnering cross-functionally with automation, analytics, and software engineering teams.