Lead Engineer, AI Software

Essential Duties and Responsibilities:

• Design and develop advanced AI software applications, ensuring scalability, performance, and integration with enterprise systems.
• Responsible for developing and modifying systems software (i.e., software for use in operating/controlling hardware and providing a platform for running internal end-user/business applications).
• Develop and communicate descriptive, diagnostic, predictive and prescriptive insights/algorithms.
• Apply knowledge of experimental methodologies, statistics, optimization, probability theory and machine learning using code for tool building, statistical analysis and modeling, using both general purpose software and statistical languages.
• Lead technical implementation efforts in both theoretical and product design environments, translating complex algorithms and specifications into code while mentoring junior engineers and guiding team-level development practices.

Job-Specific Essential Duties and Responsibilities:

• Design, build, ship, and operate production software systems incorporating AI and machine learning capabilities.
• Own difficult technical problems from initial exploration through implementation, deployment, troubleshooting, and continuous improvement.
• Write high-quality software and contribute directly to application code, APIs, services, automated tests, infrastructure, and engineering tooling.
• Build AI-enabled applications that integrate models, enterprise data, cloud services, APIs, and existing systems.
• Apply strong engineering practices including automated testing, CI/CD, observability, security, resiliency, and performance optimization.
• Evaluate emerging AI technologies through hands-on experimentation and determine where they can provide practical value in production.
• Build reusable components, libraries, patterns, and reference implementations that help other teams deliver better software.
• Mentor other engineers through code reviews, pairing, design discussions, and shared problem solving.

Minimum Requirements

• Bachelor’s degree in relevant field of study and 7+ years of relevant professional experience required, or equivalent combination of education and experience.

Job-Specific Minimum Requirements:

• 7+ years of professional software engineering experience, including substantial experience building and supporting production systems.
• 3+ years of experience with artificial intelligence, machine learning, or related technologies.
• 5+ years of experience designing or building solutions in cloud environments.
• Demonstrated experience owning software through deployment, production operations, troubleshooting, maintenance, and evolution.
• Strong software engineering fundamentals, including system and API design, testing, source control, and secure development.
• Experience designing and implementing systems on AWS, Azure, GCP, or similar cloud platforms.
• Experience with modern software delivery practices including automated testing, CI/CD, infrastructure automation, and observability.
• Experience building or integrating AI/ML capabilities into software systems or demonstrated ability to quickly learn and apply emerging technologies.
• Ability to communicate technical decisions, tradeoffs, and risks clearly with technical and non-technical colleagues.
• US Citizenship required.
• Must have the ability to obtain a Public Trust.

Preferred Skills and Qualifications:

• Deep expertise in Python, demonstrated through substantial production software rather than scripts, notebooks, or prototypes alone.
• Proficiency in at least one systems programming language, such as Rust, Go, C++, or C, with experience applying it to real-world software engineering problems.
• Experience building and operating distributed or cloud-native production systems.
• A track record of taking systems from initial development through production and ongoing operation.
• Experience diagnosing complex production problems across application, infrastructure, data, and integration boundaries.
• Experience designing APIs, services, asynchronous workflows, and system integrations.
• Practical experience building applications using large language models, machine learning models, or managed AI services.
• Experience working in environments where security, privacy, reliability, or regulatory requirements influence engineering decisions.
• Experience improving existing systems and leaving codebases safer, simpler, more reliable, or e…