Associate Director Engineering (Hybird)

Job description

Job Description Associate Director, Digital Operations Agentic Intelligence (m/f/d) Digital is the multiplier that will allow Development Sciences and Clinical Supply (DSCS) to deliver better experiments faster, efficient filing and launch, more robust supply chains and higher-confidence decisions across the portfolio. The DSCS Digital Technologies (DDT) organization is tasked with the mission to pioneer and deploy innovative digital technologies that drive the acquisition, automation and utilization of data to enhance insights, efficiency, and quality of DSCS processes and methods. The Associate Director, Digital Operations Agentic Intelligence is a senior technical leader within the Agentic Intelligence team, responsible for advancing the organization’s shift from traditional business intelligence and manual reporting toward governed, AI-ready data foundations and production-grade intelligent agents. The role pairs deep technical judgment with business acumen: identifying where agentic AI and decision intelligence create the greatest value, shaping the solutions that deliver it, and ensuring those capabilities are trusted, adopted, and sustained across DSCS. This is a role for an experienced leader who operates with a high degree of independence, owning definable programs end to end, setting technical direction, prioritizing based on business value and risk, coaching talent, and contributing directly or indirectly to the strategy of the Agentic Intelligence group. The Associate Director remains credible and current across the modern data and AI stack, including Python, SQL, Databricks, Dataverse, Power BI, GitHub, Copilot Studio, Gemini/Vertex AI or comparable enterprise AI platforms, and Microsoft Power Platform, and applies that depth to solution architecture, design review, and evaluation as much as to hands-on delivery. The Associate Director, Digital Operations Agentic Intelligence will: Shape and advance the agentic intelligence agenda for DSCS Digital Operations, identifying where agents, data products, and automation create the greatest business value, and translating that into a prioritized, sequenced roadmap. Own definable projects and programs across their full lifecycle, including design, build, evaluation, deployment, adoption, and sustainment, for governed data products, reporting solutions, automations, and intelligent agents. Exercise independent technical and business judgment on what to build, what to standardize, what to retire, and what to decline, balancing value, risk, effort, and long-term maintainability. Translate complex business challenges into technical roadmaps, solution designs, agent architectures, evaluation frameworks, and measurable outcomes, anticipating stakeholder needs. Establish and champion disciplined engineering and governance standards, including version control, documentation, testing, reusable patterns, and release-readiness controls, so solutions scale beyond their original use case. Lead teams and projects, act as a resource across multiple areas, and identify, train, and coach talent to raise the capability of individuals and the group. Partner with business leaders to drive adoption and demonstrate value realization, so success is measured by decisions improved and outcomes delivered, not solutions shipped. Key Responsibilities: Agentic AI Strategy & Delivery: Direct the design, delivery, and lifecycle governance of intelligent agents and AI-enabled workflows, establishing reusable patterns and appropriate human oversight. AI-Ready Data Foundations: Set direction for the data pipelines, semantic layers, and reusable data products that make DSCS data trusted, discoverable, and fit for AI-enabled use. Business Intelligence, Applications & Automation: Oversee delivery of dashboards, applications, and workflow automations that allow users to act on insights within their day-to-day processes. Solution Architecture & Design Review: Define reference architectures and integration patterns for agentic and data solutions, and lead design reviews that ensure choices are sound, scalable, and consistent across the team. Decision Intelligence & Value Realization: Collaborate with the Decision Intelligence and Change Management team to align agentic and data solutions to established decision frameworks, KPIs, and adoption measures, and supply the delivery and usage evidence needed to demonstrate business value. Evaluation, Quality & Responsible Deployment: Establish evaluation and testing standards for agents, data, and reporting solutions so they remain accurate, monitored, secure, and responsibly deployed. Engineering Standards, CI/CD & Release Management: Establish source control, code review, automated testing, and CI/CD practices, and define the gated promotion path from development through test to production so releases are repeatable, evidenced, and approved. Documentation & Knowledge Management: Set the standard for design documents, runbooks, decision logs, and handover materials so solutions are transferable, supportable, and not dependent on any single individual. Production Operations, Monitoring & Support: Own the sustainment model for deployed solutions, including performance monitoring, issue triage, user support, and the retirement or rework of capabilities that no longer deliver value. Security, Compliance & Data Governance: Partner with data product owners, enterprise IT, cybersecurity, privacy, and quality functions to ensure solutions meet access control, data classification, auditability, and GxP or regulatory expectations where applicable. Team Leadership & Talent Development: Lead project teams, mentor engineers and analysts across varied technical backgrounds, and raise the technical bar through coaching, code review, and shared learning. Innovation & Emerging Technology Evaluation: Stay current on emerging models, platforms, and agentic patterns, run structured evaluations, and recommend where new capabilities should be adopted, piloted, or deferred. Required Experience and Skills: Experience: 7+ years of experience in data engineering, software development, business intelligence, data science, AI/ML, or a related technical field, including demonstrated experience leading projects and/or teams (Ph.D. with 4+ years, M.S. with 6+ years, or B.S. with 7+ years of relevant experience). Technical Depth & Credibility: Hands-on expertise with Python and SQL, with the technical standing to architect, review, challenge, and optimize solution designs, data models, code, and queries across data transformation, analysis, automation, and reporting use cases. Data Engineering Foundation: Deep working knowledge of data pipelines, data modeling, data quality, semantic layers, metadata, lineage, and structured data products, with experience in Databricks, Dataverse, cloud data platforms, or comparable enterprise data environments. Agentic AI & LLM Solutions: Demonstrated experience building and orchestrating Generative AI, Large Language Model, and agentic workflow solutions using Copilot Studio, Gemini/Vertex AI, Microsoft Power Platform, retrieval-augmented generation, workflow orchestration, and responsible AI practices, including agent evaluation and monitoring. Engineering Practices: Strong command of GitHub or comparable source-control systems, including repositories, branching, pull requests, code review, version control, and CI/CD, with hands-on experience using AI coding assistants and coding agents (e.g., GitHub Copilot, Claude Code, Cursor) to accelerate delivery, including the judgment to review, test, and validate AI-generated code. Business Value & Decision Judgment: Demonstrated ability to prioritize and sequence work based on business value, risk, and feasibility; define KPIs, adoption metrics, and value realization measures; and make defensible decisions about what to advance, standardize, or retire in partnership with business stakeholders. Testing, Evaluation & Governance Minds