Lead Engineer, AI Software

Maximus

8d•$180,000 - $200,000•Remote

About The Position

Maximus is seeking a Lead AI Systems Engineer to join the Maximus AI Transformation and Experience team. This role involves building software and AI capabilities for enterprise-wide use and government programs. It is a hands-on individual contributor position focused on designing, building, testing, deploying, and improving software, with AI and machine learning being key components. The successful candidate will work with a team of engineers and specialists on challenging problems, contributing to meaningful improvements in employee efficiency and citizen services. This is a remote position.

Requirements

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

Nice To Haves

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 easier to operate.
Experience mentoring engineers through collaboration, code reviews, and technical problem solving.

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.
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.