Lead development teams to ensure sprint commitments are met
Define and maintain AI technical standards, reference architectures, prompt libraries, templates, and playbooks
Partner with sales and delivery to design AI strategies, architectures, and proof of concepts
Architect and deploy MLOps/AIOps platforms that support model lifecycle management, evaluation, and monitoring
Develop and deliver AI training programs, workshops, and internal documentation

Requirements

8–12+ years of professional experience in software engineering and system architecture
Strong background in MLOps, model lifecycle management, and evaluation frameworks
Proficiency with modern AI/ML frameworks and cloud based AI platforms
Comfortable presenting complex AI concepts to technical and non-technical stakeholders
Demonstrated experience mentoring engineers and elevating team capabilities
May include intensive programs, Bachelor’s degree in Computer Science, Engineering, or equivalent experience

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

MLOpsmodel lifecycle managementAI frameworksML frameworkscloud based AI platformssoftware engineeringsystem architecture

Soft Skills

mentoringpresentation skillsteam capabilities enhancement

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in Engineering