Director, Full Stack Software Engineering & AI

We are seeking a Full Stack Software Engineering & AI to lead the endtoend data product, analytics, and AI transformation of our Life Sciences & Healthcare portfolio. This is a unique opportunity to define and scale customerfacing data products built on strong software engineering foundations, robust data modeling, and productiongrade AIadvancing drug discovery, realworld 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

Bachelors or Masters 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 softwareengineered, 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 highperformance 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 architecturelakehouse, 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 productspredictive 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 .