Director, Agentic Lab

Accountabilities:

• • Lead rapid prototyping, experimentation, and technical validation of agentic AI solutions, autonomous workflows, and emerging AI capabilities.
  • Evaluate foundation models, agent frameworks, orchestration technologies, developer tooling, and related technologies to identify opportunities for enterprise adoption.
  • Develop reusable proof-of-concepts, accelerators, reference architectures, and implementation patterns that can support broader AI engineering initiatives.
  • Partner with AI Engineering, Platform Engineering, Product, Architecture, and other technical teams to transition successful prototypes into production-grade enterprise capabilities.
  • Establish best practices for prompt engineering, reasoning strategies, agent memory architectures, evaluation frameworks, observability, and autonomous workflow design.
  • Contribute to enterprise-wide standards, technical documentation, engineering guidelines, and reusable patterns for developing and deploying AI agents.
  • Help assess technical feasibility, scalability, reliability, and business value of emerging agentic AI approaches.
  • Identify opportunities to improve AI development workflows through experimentation with new models, tools, frameworks, and automation techniques.
  • Mentor AI engineers and technical contributors, promoting strong engineering practices, knowledge sharing, experimentation, and continuous learning.
  • Collaborate across research, engineering, architecture, product, and business functions to communicate technical possibilities, trade-offs, and recommendations.
  • Support the evolution of an enterprise AI ecosystem by helping establish scalable development practices and technical foundations for agentic applications.

  Requirements:

  • Bachelor’s or advanced degree in Computer Science, Artificial Intelligence, Engineering, or a related technical discipline.
  • 7+ years of experience building AI, machine learning, or software engineering solutions, including experience providing technical leadership.
  • Strong hands-on expertise with large language models (LLMs), agent frameworks, retrieval-augmented generation (RAG), vector databases, APIs, Python, and cloud-native development.
  • Demonstrated software engineering expertise with experience designing and delivering production-grade AI applications and scalable technical solutions.
  • Experience evaluating emerging AI technologies and translating experimental concepts into practical, reusable, and production-oriented implementations.
  • Strong understanding of agentic AI concepts, autonomous workflows, orchestration, prompt engineering, reasoning strategies, memory architectures, evaluation, and observability.
  • Excellent communication and collaboration skills, with the ability to work effectively across research, engineering, architecture, product, and business teams.
  • Demonstrated ability to mentor technical professionals and influence engineering practices across teams.
  • Strong curiosity, learning agility, analytical thinking, and willingness to experiment with rapidly evolving AI technologies.
  • Ability to connect technical innovation with business value and enterprise-scale requirements.
  • Experience with data quality, data governance, data literacy, machine learning algorithms, statistical analysis, or related AI disciplines is advantageous.
  • Experience in pharmaceutical, healthcare, or another highly regulated industry is preferred.
  • Experience building enterprise agentic AI platforms, developer ecosystems, or reusable AI infrastructure is highly desirable.

  Benefits:

  • Base salary: $194,600–$361,400 USD per year, with final compensation based on factors including relevant skills and experience and subject to periodic review.
  • Performance compensation: Eligibility for a performance-based cash incentive.
  • Equity: Depending on role level, eligibility to be considered for annual equity awards.
  • Healthcare: Comprehensive health benefits for eligible US employees.
  • Insurance: Life and disability coverage.
  • Retirement: 401(k) plan with employer contribution and matching.
  • Paid time off: Generous vacation, personal days, holidays, and other applicable leave programs.
  • Remote anywhere in the United States, subject to applicable legal-entity restrictions.
  • Travel: Approximately 10% domestic and/or international travel.
  • Professional growth: Opportunity to mentor technical talent, work with emerging AI technologies, and contribute to enterprise-scale innovation.
  • Inclusive environment: A collaborative culture centered on experimentation, continuous learning, diverse perspectives, and innovation.