Manager, Software Engineer

Responsibilities

• Lead, mentor, and grow a team of AI software engineers, fostering a culture of technical excellence, ownership, and continuous learning.
• Drive engineering execution by establishing priorities, managing delivery, and ensuring predictable, high-quality outcomes.
• Define the technical architecture and engineering direction for AI platforms, services, and enterprise applications.
• Partner with Product, Design, Data Science, Security, and business stakeholders to translate business objectives into scalable technical solutions.
• Architect, build, and oversee the delivery of production-grade AI services with a focus on reliability, scalability, observability, and operational excellence.
• Guide the implementation of modern AI capabilities, including retrieval-augmented generation (RAG), AI agents, orchestration frameworks, and integrations with leading LLM providers.
• Establish engineering best practices for software development, testing, deployment, code quality, and operational support.
• Remain technically engaged by reviewing architecture, mentoring engineers, and contributing to key technical decisions and complex implementations when appropriate.
• Recruit, coach, and develop engineering talent while helping shape the long-term growth of the AI Engineering organization.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Physics, Mathematics, or a related technical field.
• 8+ years of professional software engineering experience, including at least 3+ years leading engineering teams.
• Proven experience building, delivering, and operating production software systems at scale.
• Experience leading engineering teams responsible for AI/ML-enabled products or platforms.
• Strong hands-on experience developing production applications in Python.
• Deep understanding of modern AI and machine learning concepts, including large language models (LLMs), retrieval-augmented generation (RAG), AI agents, and model orchestration frameworks.
• Experience integrating AI services using leading LLM providers and modern AI frameworks such as LangChain, LangGraph, or similar technologies.
• Experience designing cloud-native applications using AWS, Docker, and modern deployment and CI/CD practices.
• Experience with relational databases (PostgreSQL preferred) and distributed application architectures.
• Strong understanding of software engineering best practices, including testing, observability, security, code review, and operational excellence.
• Demonstrated ability to recruit, mentor, and develop high-performing engineering teams.
• Excellent communication and collaboration skills with the ability to influence technical and non-technical stakeholders.
• Experience working in Agile development environments using tools such as GitHub, Jira, and Jenkins (or equivalent).

Nice-to-Haves

• Experience in financial technology or regulated industries.
• Startup or high-growth company experience.
• Experience building and scaling AI platforms used across multiple products or business functions.
• Experience leading engineering organizations through rapid growth or organizational change.