Director, Full Stack Software Engineering & AI

Job description

We are seeking a Full Stack Software Engineering & AI to lead the end‑to‑end data product, analytics, and AI transformation of our Life Sciences & Healthcare portfolio. This is a unique opportunity to define and scale customer‑facing data products built on strong software engineering foundations, robust data modeling, and production‑grade AI—advancing drug discovery, real‑world evidence, patient journey modeling, and treatment effectiveness analytics. You will own the data product strategy, dimensional data architecture, engineering standards, platform design and AI roadmap , ensuring our data products are trusted, performant, discoverable, and monetizable. About You – Experience, Skills & Accomplishments Minimum 15+ years in data engineering, software engineering, analytics, or data product leadership, including 4+ years managing managers and global teams Proven success building and scaling enterprise-grade data products using software engineering and data modeling best practices Deep experience embedding AI, ML, and GenAI into data-centric and analytics-driven products Strong data modeling expertise: Dimensional modeling (facts & dimensions) Star and snowflake schema design Conformed dimensions and analytical data models Modeling for BI, analytics, and AI/ML workloads Experience creating domain-oriented data models, semantic layers, and metrics frameworks Hands-on or architectural experience with cloud-native development (AWS, Azure, or GCP) and data platform engineering Proficiency in Python, Java, SQL, microservices, and data-centric application development Good knowledge of AWS services (EC2, Lambda, S3, RDS), Docker, Kubernetes, and CI/CD for data/AI workloads Expertise with modern data platforms (Snowflake, Databricks, lakehouse architectures, Spark, and streaming frameworks ) Background in AI/ML frameworks (TensorFlow, PyTorch), MLOps, feature stores, and model lifecycle management will be a plus Experience with Generative AI, LLMs, RAG architectures, agentic systems, and MCP (Model Context Protocol) a strong plus Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field Bonus Points Experience delivering commercial data-as-a-product or analytics offerings Familiarity with Life Sciences/Healthcare domains (RWE, clinical, or commercial data models) Strong passion for customer outcomes, product thinking, and measurable business impact What You Will Be Doing Data Product, Analytics & AI Strategy Lead and scale a global organization of 30+ engineers delivering large-scale, mission-critical data products trusted by top 20 global pharmaceutical companies Define and drive the data product, analytics, and AI roadmap across the LSH portfolio Partner with product and business leaders to design analytics-ready, customer-centric data products Establish data product ownership, SLAs, quality KPIs, and lifecycle management Ensure governance, privacy, and compliance are embedded by design Software Engineering & Data Modeling Lead the design and delivery of software‑engineered, modular, API-first data products Own enterprise analytical data models, including dimensional models, star/snowflake schemas, conformed dimensions, and reusable metrics Ensure data models support high‑performance analytics, BI, ML, and GenAI use cases Champion engineering excellence: test automation, CI/CD, observability, data quality, performance optimization Data Platform & Analytics Engineering Own cloud data platform architecture—lakehouse, streaming, and real-time analytics capabilities Enable semantic modeling, analytics engineering, and self-service BI through trusted dimensional models Define standards for data quality, lineage, metadata, discoverability, and metric consistency Optimize models for scalability, cost efficiency, and performance AI, GenAI & Intelligent Data Products Lead development of AI-powered data products—predictive analytics, GenAI, and LLM-based experiences Drive MLOps and LLMOps to operationalize AI at scale Explore advanced capabilities such as metrics-aware LLMs, semantic search over dimensional models, and agentic analytics Leadership & Team Development Build, mentor, and grow a high-impact global team across data modeling, data engineering, ML engineering, and platform engineering Foster a data-model-driven, product-centric, engineering-first culture Lead hiring, talent development, and performance management Collaboration & Influence Partner with product, data science, BI, and business leaders to align metrics, dimensions, and analytical logic Communicate data product strategy, modeling decisions, and AI outcomes to senior executives About the Team You will join the Life Sciences & Healthcare Commercial Product Engineering organization, leading a globally distributed team across India and the United States focused on delivering high-quality, AI-powered, well-modeled data products at scale. Hours of work Full-time Hybrid working model At Clarivate, we are committed to providing equal employment opportunities for all qualified persons with respect to hiring, compensation, promotion, training, and other terms, conditions, and privileges of employment. We comply with applicable laws and regulations governing non-discrimination in all locations.