We are seeking an experienced AI/ML Engineering Lead to drive enterprise AI initiatives, AI platform delivery, and AI Development Lifecycle (AIDLC) transformation. The ideal candidate will have strong hands-on experience in AI/ML engineering, enterprise AI solution implementation, and leading or mentoring AI/ML engineering teams.
Key Responsibilities
- Lead, manage, mentor, and coach AI/ML engineering teams, with a strong focus on AIDLC-based delivery.
- Drive enterprise AI transformation and AI platform modernization initiatives.
- Design, develop, and implement scalable AI/ML solutions for enterprise environments.
- Establish and improve AI Development Lifecycle (AIDLC) processes, frameworks, and engineering practices.
- Work with AIDLC frameworks such as Spec Kit, BMAD, Spectra, or similar AI development methodologies.
- Collaborate with architecture, engineering, data, security, and business teams to deliver AI solutions.
- Define and implement responsible AI practices, including governance, transparency, explainability, and risk controls.
- Support model risk management and regulatory compliance requirements.
- Establish best practices for AI/ML development, testing, deployment, monitoring, and lifecycle management.
- Evaluate emerging AI/ML technologies and recommend appropriate enterprise adoption strategies.
- Lead AI platform delivery and integration across enterprise technology environments.
- Support modernization of existing platforms and applications using AI/ML capabilities.
- Ensure AI solutions meet enterprise security, privacy, compliance, scalability, and performance requirements.
- Communicate technical strategies, architecture decisions, and AI transformation roadmaps to senior stakeholders.
Required Skills
- 8–10 years of overall experience in technology, with 6–8 years of experience in AI/ML.
- Minimum 4 years of experience leading, managing, or coaching AI/ML engineering teams.
- Strong experience in AI/ML engineering and enterprise AI solution implementation.
- Strong understanding of AI Development Lifecycle (AIDLC).
- Experience with AIDLC frameworks and methodologies such as Spec Kit, BMAD, Spectra, or comparable frameworks.
- Experience delivering and managing enterprise AI platforms.
- Strong understanding of AI governance and responsible AI practices.
- Experience with model risk management and regulatory/compliance requirements.
- Experience leading enterprise AI transformation or platform modernization initiatives.
- Strong communication, stakeholder management, and technical leadership skills.
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related field.
- Certifications in AI/ML, Cloud, Data Engineering, or Agile methodologies.
- Experience working within healthcare, financial services, or other highly regulated enterprise environments.
- Experience with cloud-based AI/ML platforms and enterprise data ecosystems.
- Experience establishing AI governance, risk, and compliance processes.