Manager Software Engineering (AI Team)

About the Role

Key Responsibilities

• Lead, mentor, and develop a team of 10+ AI/ML software engineers, fostering a culture of growth, collaboration, and technical excellence. Ensure high performance by providing regular feedback, coaching, and career development opportunities.
• Oversee the design and delivery of AI and generative AI systems, ensuring solutions are scalable, robust, and high-quality. Guide your team to implement innovative AI models, tools, and infrastructure that drive business outcomes.
• Partner with other engineering leaders, data scientists, product managers, and directors to align on strategic goals and deliverables. Collaborate closely with cross-functional teams to break down complex engineering tasks and drive the AI roadmap.
• Lead your team in an agile environment, participating in sprint planning, daily stand-ups, code reviews, and retrospectives. Help the team manage competing priorities while maintaining focus on delivering high-quality AI solutions.
• Promote best practices in software development, code quality, testing, and deployment. Drive the adoption of modern engineering practices like CI/CD, automated testing, and cloud-based AI/ML solutions.
• Stay up to date with the latest advancements in Generative AI and machine learning. Foster a culture of continuous learning, encouraging engineers to grow their technical skills and experiment with emerging technologies.
• Act as a liaison between the AI team and other stakeholders, effectively communicating progress, risks, and technical insights to non-technical leadership and product teams.

Requirements

• 7-10 years of experience in software engineering, with at least 2-4 years in a leadership or management role overseeing AI or machine learning teams.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Strong experience with AI, machine learning, and deep learning technologies, as well as understanding of the software development lifecycle, object-oriented programming, concurrency, design patterns, RESTful services, and microservice architecture.
• Experience with cloud platforms (AWS, Google Cloud, Azure), focusing on AI/ML deployment (e.g., VertexAI, GKE, BigQuery, Kubeflow, TensorFlow Serving).
• Familiarity with MLOps practices and tools for model deployment and monitoring (e.g., Terraform, GitHub Actions, Concourse).
• Strong people management and leadership skills, with experience leading cross-functional teams.
• Proven ability to mentor engineers, manage competing priorities, and align team efforts with business objectives.
• Strong understanding of agile methodologies, with experience leading teams in an agile environment.
• Excellent verbal and written communication skills, with the ability to communicate complex technical concepts to non-technical stakeholders.

Nice to Have

• Experience working with large language models (LLMs) or fine-tuning open-source models like GPT.
• Familiarity with modern AI development tools, such as Jupyter notebooks, Kubernetes, Docker, and CI/CD pipelines.
• Experience in high-compliance or enterprise-grade environments with a focus on AI ethics, privacy, and security.

Qualifications

• Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field.
• Ph.D. is a plus.