Associate Director / Director, Data & AI Solution Development

About Us

Kardigan is a heart health company working to make cardiovascular disease preventable, curable and no longer the leading cause of death in the world.

It is Kardigan’s mission to develop multiple targeted treatments in parallel that bring people with cardiovascular diseases to the cures they deserve.

Led by Tassos Gianakakos, Jay Edelberg, M.D., Ph.D., and Bob McDowell, Ph.D., Kardigan’s co-founders have reunited after leading MyoKardia to discover and develop mavacamten, the first cardiac myosin inhibitor, resulting in an acquisition by Bristol Myers Squibb in 2020.

We have a cutting-edge discovery and translational research platform, a pipeline of late-stage candidates, and an industry-leading team that is driven to improve the lives of patients.

At Kardigan, we are motivated by our values which guide how we work, interact, and achieve our goals. Driven by patients and their families , we are deeply committed to improving the lives of patients and prioritizing their needs above all else. We believe in being authentic —leading with truth to bring out the best in others by creating an environment where every person knows they will be fully accepted. With an eagerness to learn , we encourage the highest levels of curiosity and are open to changing our minds. We are committed to winning as a team with urgency, excellence, and intention, and support each other no matter what role we play or where we sit. Lastly, we strive to enable the impossible because patients are counting on us. We are not afraid to take risks to unlock innovation and advance scientific discoveries.

These values are the foundation of our work, empowering us to make a real difference, every day.

About the Team

Kardigan's Information Technology team is at the forefront of enabling innovation across the enterprise. We partner closely with colleagues throughout the entire enterprise to deliver secure, reliable, and forward-looking technology solutions that accelerate execution and unlock the power of data and artificial intelligence.

Our team is passionate about solving complex business challenges through technology. We foster a culture of collaboration, ownership, continuous improvement, and curiosity, where team members are empowered to introduce new ideas, modernize ways of working, and help shape the future of a growing biotechnology company. If you are excited by the opportunity to build, innovate, and make a tangible impact, you'll find a rewarding environment at Kardigan.

Main Responsibilities

The Associate Director / Director, Data and AI Solution Development is a solution-design leader responsible for defining and shaping Kardigan's enterprise data and AI solutions — translating business, scientific, and operational needs into well-architected solution designs, data models, and integration patterns. This role owns solution architecture, requirements analysis, and design for initiatives spanning data products, enterprise data management, and AI-enabled applications, and partners closely with the Solution Delivery team, which owns build and deployment, and the Data Platform Engineering team, which owns the underlying platform's build and operations.

A core focus of this role is designing solutions that make enterprise data usable as high-quality context for human and AI — defining the requirements and designs that ensure data feeding LLMs, RAG systems, analytics copilots, and other AI/ML applications is accurate, well-governed, and discoverable, so that partner teams can build and operationalize it with confidence. More broadly, this role is a driver of Kardigan's technology-enabled transformation, helping the organization innovate through technology and treat data and AI as strategic assets rather than cost centers. They will shape how emerging data and AI capabilities translate into real competitive advantage — accelerating R&D, improving decision-making, and differentiating Kardigan as a modern, data-driven biopharma company.

This individual will operate primarily as a solution architect and designer: setting solution architecture standards, running requirements analysis and design workshops, and partnering with business and scientific stakeholders to shape data and AI solutions. Execution and delivery are owned by a dedicated Solution Delivery team, and platform build/operations are owned by Data Platform Engineering; this role is the design authority that bridges the two, reporting to the Executive Director overseeing Data, AI & Technology and serving as a strategic peer to Data Science/Analytics and AI leadership.

Enterprise Solution Architecture & Design

Lead solution architecture and design for enterprise data and AI initiatives — translating business and scientific requirements into technical solution designs, data models, and integration patterns

Define solution patterns, reference architectures, and reusable templates for data and AI solutions that the Solution Delivery team and Data Platform Engineering can build from

Own requirements definition and business analysis for complex, cross-functional data and AI initiatives, partnering closely with business and scientific stakeholders to clarify and document needs

Develop proof-of-concepts, prototypes, and solution blueprints to validate approaches and de-risk designs before handoff to the Solution Delivery team; Define acceptance criteria and solution success measures that the Solution Delivery team uses to validate what is built

Own and prioritize the enterprise data and AI solutions roadmap and intake process, in partnership with business, scientific, and technology stakeholders

Data & AI Solution Foundations

Partner with the Data Platform Engineering team and Enterprise Architecture team to define the data, API, and platform requirements needed to support new solution designs, including data APIs, semantic interfaces, and access patterns for both human users and AI agents

Define solution-level requirements for the semantic layer — governed metric definitions, lineage, and natural-language access patterns — so that human users and AI agents can reliably consume enterprise data

Advise on where the enterprise data warehouse/lakehouse, orchestration layers, and streaming infrastructure need to evolve to support new solution designs, partnering with the platform engineering function that owns their build and operation

Define requirements for low-latency and near-real-time data access needed to support time-sensitive solution use cases

Evaluate emerging data and AI tooling (e.g., MCP servers, vector databases, low-code/no-code platforms) for fit with upcoming solution designs, in partnership with Data Platform Engineering

Enterprise Data Management

Define enterprise data management requirements and standards — data governance, master data management (MDM), metadata management, cataloging, and lineage

Define and enforce enterprise data standards, taxonomies, and ontologies that drive data quality, consistency, and discoverability across solutions

Partner with functional data owners (R&D, Clinical, Commercial, Finance, G&A) and data stewardship programs to ensure solution designs reflect accountability for data quality and integrity

Ensure solution designs comply with applicable regulatory and public-company requirements, including FDA 21 CFR Part 11, data integrity (ALCOA+) principles, GDPR/HIPAA as applicable, and SOX-relevant data controls appropriate for a newly public company

Partner with Legal, Regulatory Affairs, Quality, and Internal Audit to embed data integrity, privacy, and access-control requirements into every data and AI solution design

Data Products & Solutions-as-a-Service Design

Define the vision and design for enterprise data products — curated, documented, reusable datasets and APIs — delivered as a service to business, scientific, and technology teams

Design the solution and data product intake model (