Director, AI Engineering and Enablement

Position Summary

• Lead the architecture, design, and implementation of scalable Enterprise AI applications.
• Drive the technical strategy for GenAI solutions, ensuring robust integration, security, and performance across the organization.

• Architect, design, and build end-to-end GenAI applications.
• Define solution architectures leveraging cloud platforms (AWS, Azure, GCP) for scalability, reliability, and security.
• Present and propose technical solutions that fit requirements.
• Plan and coordinate project deliveries to meet timelines and business needs.
• Develop core features and infrastructure; write production-grade code in Python, React, and other languages as needed.
• Lead implementation of best software engineering practices (modularity, version control, CI/CD, automated testing).
• Perform code and architecture reviews to ensure robust, maintainable, high-performing solutions.
• Drive adoption of engineering best practices across the organization.
• Set standards for thorough, clear documentation of architectures, processes, and code.
• Directly manage engineers (senior & junior): hiring, onboarding, and day-to-day activities.
• Provide technical mentorship; foster a culture of innovation, learning, and inclusiveness.
• Set clear objectives, track progress, and conduct regular performance reviews.
• Research, design, and implement agentic AI solutions using Lang Chain and Lang Graph.
• Build autonomous genAI agents for reasoning, multi-step workflows, and tool-usage.
• Optimize agent performance, reliability, and compliance for enterprise production.
• Evaluate emerging AI techniques/tools/frameworks and make strategic recommendations.
• Develop React user interfaces; integrate front-end with back-end APIs and AI models.
• Collaborate with UX/UI teams to drive adoption and usability.
• Maintain and evolve RESTful APIs and microservices architecture.
• Deploy, monitor, and maintain AI applications using cloud-native infrastructure, containers, CI/CD, and observability tools.
• Oversee cloud resources for cost optimization and performance.

• Bachelor’s or Master’s in Computer Science, Engineering, or related field.
• 7+ years in software/AI engineering.
• 3+ years leading technical teams.
• Proven experience developing and deploying enterprise applications in AWS, Azure, and GCP.
• Advanced skills in Python and React; familiarity with GenAI frameworks (e.g., Lang Chain, Lang Graph).
• Strong understanding of AI application lifecycle, security, compliance, and performance optimization.
• Excellent communication, leadership, and project management skills.

• Health Coverage: medical, pharmacy, dental, vision.
• Wellbeing Support: BMS Well-Being Account, BMS Living Life Better, EAP.
• Financial Well-being and Protection: 401(k), short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, survivor support.
• Work-life:
  Paid Time Off (flexible/unlimited for US exempt employees; 160 hours annual paid vacation for certain roles; plus paid national holidays as described; additional time off may include sick time, volunteer days, summer hours, leaves of absence, and annual Global Shutdown).

• Site-essential: 100% of shifts onsite.
• Site-by-design: hybrid with at least 50% onsite (onsite presence is essential).
• Field-based/remote-by-design: ability to travel onsite to visit customers/patients/partners and attend meetings as directed.