Senior AI Manager

Responsibilities

• Lead and build high-performing AI teams focused on model development, deployment, and lifecycle management.
• Establish and scale MLOps practices, including CI/CD for ML, model/version management, monitoring, retraining, and platform standardization.
• Evaluate and integrate external AI technologies, tools, and vendors, guiding build vs buy decisions.
• Drive design sprints specific to NPI problem statement to show AI-driven quality, cost, timelines, and business outcomes.
• Ensure successful delivery of AI initiatives aligned to quality, cost, timelines, and business outcomes.
• Drive AI strategy, roadmap, and adoption across products and enterprise platforms.
• Collaborate with cross-functional teams (Product, Engineering, Architecture, Data, Security) to integrate AI capabilities into business solutions.
• Identify and implement AI-driven innovations and productivity improvements (automation, optimization, predictive intelligence).
• Lead model governance, ethical AI practices, and compliance frameworks.
• Provide technical and strategic leadership in key areas such as deep learning, generative AI, NLP, computer vision, and predictive analytics.
• Mentor and coach team members, fostering a culture of continuous learning and innovation.
• Drive stakeholder alignment, communicate insights, and influence executive decision-making.
• Anticipate risks and proactively resolve challenges across AI initiatives.
• Support proposals, innovation initiatives, and competitive differentiation using AI.

Qualifications

• Bachelor’s degree from an accredited institution in a technical discipline such as science, technology, engineering, mathematics.
• 8+ years of experience in software engineering, data science, or software development.
• 2+ years leading technical teams in AI or advanced analytics.
• Strong expertise in machine learning, deep learning, and AI system design.
• Understanding of Do-178B SDLC.
• Experience delivering production-scale AI solutions.
• Strong problem-solving, analytical, and decision-making skills.
• Excellent communication and stakeholder management skills.

We Value

• Bachelor’s degree in Computer Science, software engineering, Data Science, Engineering, or related field.
• Experience with Generative AI, LLMs, and foundation models.
• Knowledge of MLOps, model lifecycle management, and AI platform engineering.
• Experience with cloud platforms (Azure AI, AWS, GCP) and scalable AI architectures.
• Understanding data engineering, feature engineering, and big data ecosystems.
• Experience implementing responsible AI, explainability, and governance frameworks.
• Strong leadership in driving organizational change through AI adoption.
• Ability to manage complex programs, multiple priorities, and cross-functional teams.
• Proven ability to influence strategy and deliver measurable business outcomes.

U.S. Person Requirements

Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.