• Own end-to-end execution of AI and automation POCs, from idea to validation • Rapidly test tools, frameworks, and agentic workflows to solve business problems • Iterate quickly prioritize speed, learning, and business impact over perfection • Design and implement agentic workflows using modern AI tools (LLMs, copilots, automation platforms) • Identify opportunities to automate repetitive or manual processes across teams • Continuously refine workflows to improve efficiency and scalability • Act as the bridge between business teams and technical teams • Translate business pain points into actionable AI use cases • Partner closely with DevOps to ensure solutions are practical, secure, and cost-effective • Define and track KPIs for AI initiatives (e.g., time savings, cost reduction, adoption) • Support leadership and Board-level visibility into AI initiatives and impact • Evaluate tools and architectures with a strong focus on cost efficiency • Make decisions on build vs. buy vs. integrate approaches • Collaborate with dedicated DevOps resources to optimize deployments • Highly proactive and self-driven • Comfortable operating in ambiguity and fast iteration cycles • Strong communicator who can influence across teams • Focused on business impact, not just technical output.

• Own the full lifecycle of Code for America's AI Acceptable Use Policy: drafting foundational policy from the ground up, socializing it across the organization, driving adoption, and revising it on an ongoing basis as tools, risks, and best practices evolve • Advise on the employee-facing implications of AI tool deployment, including acceptable use boundaries, monitoring practices, and policy provisions that intersect with employment law and workforce relations — working in close coordination with People Operations and Legal. • Write governance frameworks and policy documents in accessible, plain-language formats — ensuring that staff at all levels and across all disciplines can understand and act on guidance, not just compliance and IT teams • Serve as an internal consultant to teams in the early stages of exploring, piloting, or refining AI-assisted workflows — guiding experimentation with a "yes, and here's how to do it safely" orientation • Document and share learnings from team-level pilots to build organizational knowledge and surface replicable patterns • Act as a liaison between IT/security and non-technical program and operations teams, translating between contexts and representing staff needs when governance or tooling decisions are being made • Partner with People Operations and Legal on the development and ongoing review of AI-related employment policies, including policies that govern employee conduct, monitoring, and use of AI tools in the workplace — ensuring governance frameworks are informed by and aligned to employee relations considerations. • Lead change management for AI-related transitions — helping staff understand not just what is changing, but why, and what it means for their work • Partner closely with Security Engineering to ensure AI governance and enablement work is integrated with the organization's broader security posture • Collaborate with compliance stakeholders and legal/People Operations as needed to assess AI tool risk, data privacy implications, and organizational policy alignment— including implications for employee relations and workforce obligations. • Monitor the evolving AI governance and security landscape and proactively recommend policy and control updates as new tools, risks, or regulations emerge • Maintain the vendor inventory, conduct lightweight third-party security reviews on new tools, and escalate higher-risk reviews to the Security Engineering team • Coordinate security awareness programming, including staff training and onboarding modules • Design, launch, and continuously improve a suite of AI enablement resources: training sessions, onboarding guides, office hours, self-serve resource hubs, and practical playbooks • Facilitate workshops and learning sessions for staff across all levels and disciplines, explaining technical concepts in accessible, jargon-free ways • Build and steward an internal AI Champions network — recruiting, supporting, and coordinating peer advocates across departments to drive adoption and share learnings • Develop onboarding materials for new staff and role-specific enablement resources for teams with specialized AI use cases • Other duties as assigned

• Identify opportunities to automate business processes. • Build and manage AI assistants using ChatGPT, Claude, Gemini, Copilot, and similar tools. • Create automated workflows using Zapier, Make, Power Automate, and other platforms. • Integrate AI tools with CRM systems and business software. • Develop AI-powered SOPs, knowledge bases, and documentation. • Analyze workflows and recommend efficiency improvements. • Automate repetitive administrative tasks. • Improve scheduling, staffing, and workforce utilization. • Create dashboards and reports to track performance and KPIs. • Streamline recruiting and onboarding processes through automation. • Implement AI-assisted candidate screening and workforce analytics. • Support employee retention and scheduling initiatives. • Automate CRM workflows, lead tracking, and follow-ups. • Develop reports, forecasts, and performance dashboards. • Provide insights and recommendations based on business data. • Support leadership with strategic projects and technology initiatives. • Prepare reports, presentations, and process improvement recommendations. • Coordinate implementation of AI and automation projects across departments.

Role Description Legend Biotech is seeking a Principal Bioinformatician as part of the Early Drug Development team based in Somerset, NJ or Remotely. This role is to support translational strategies across pipeline development programs. He/She will lead computational analyses integrating multi-modality clinical and biomarker datasets to enable mechanism-of-action understanding, patient stratification, pharmacodynamic assessment, etc. to support translational decision-making. Key Responsibilities - Translational Biomarker Analysis with multi-modality and multi-omics assays such as: - Bulk and Single cell RNA-seq - TCR/BCR-seq - WGS/WES - Amplicon-seq - ATAC-seq - ctDNA/liquid biopsy - Proteomics and cytokine profiling - Spatial and multiplex imaging - Flow cytometry/CyTOF - Support translational biomarker discovery and validation including identification of: - Pharmacodynamic (PD) biomarkers - Predictive biomarkers - Prognostic biomarkers - Response biomarkers - Build and maintain reproducible and scalable bioinformatics pipelines using cloud or high-performance computing environments. - Contribute to translational data infrastructure and data governance strategies. - Ensure analysis reproducibility, traceability, and documentation compliance. - Partner closely with Translational scientists, Clinical Development, Research and CMC teams, CROs and collaborators to help translate complex computational findings into biologically meaningful insights. - Contribute to regulatory documentation required biomarker sections of INDs, IBs, Clinical study reports and Regulatory briefing documents. - Make decisions related to methodologies and approaches development processes. - Make decisions related to project execution, including timelines, milestones and resource allocation within budget. Qualifications - PhD (5+ years) or MS (8+ years) in Bioinformatics, Computational Biology, Genomics, Systems Biology and related quantitative biological sciences. - Strong expertise in bioinformatics, statistics with some biological training background, with experience in translational research in oncology, immunology or autoimmune disease. - Gene and cell therapy involvement is a plus. - Strong experience with: - R and/or Python programming - Linux/Unix computing environments - Workflow management systems (e.g., Snakemake, Nextflow, WDL) with Cloud platforms (AWS, GCP, Azure) preferred Requirements - Experience in translational research in oncology, immunology or autoimmune disease. - Strong programming skills in R and/or Python. - Familiarity with Linux/Unix computing environments. - Experience with workflow management systems and cloud platforms. Benefits - Medical, dental, and vision insurance. - 401(k) retirement plan with a company match that vests fully on day one. - Eight (8) weeks of paid parental leave after just three (3) months of employment. - Paid time off policy including vacation time, personal time, sick time, floating holidays, and eleven (11) company holidays. - Additional voluntary benefits including flexible spending and health savings accounts, life and AD&D insurance, short- and long-term disability coverage, legal assistance, and supplemental plans. - Voluntary commuter benefits, family planning and care resources, well-being initiatives, and peer-to-peer recognition programs.