Remote AI Tech Lead

Required Skills & Experience

What You Will Need:

• Degree in computer science, data science, artificial intelligence, engineering, information systems, statistics, or a related technical field is required.
• Demonstrated senior-level experience designing and developing AI or machine learning solutions using Python and modern AI/ML frameworks, with the ability to produce, review, and troubleshoot production-quality code.
• Minimum of 3+ years’ experience architecting and deploying AI applications in cloud environments, integrating models with enterprise data sources and APIs, and applying software engineering, DevSecOps, MLOps, testing, monitoring, and documentation practices.
• Minimum of 5+ years experience leading technical development team(s) o This can be purely in a software dev lifecycle (dev-test-prod) – doesn’t need lead experience in AI
• Great communication skills.
• Must be able to work in matrixed environment.
• Experience in data engineering, software development, or related roles.
• Proven ability to lead multidisciplinary technical teams and communicate complex AI concepts, architecture decisions, risks, and recommendations to technical and non-technical stakeholders in public health, healthcare, government, or other regulated environments. 40-80h Exact compensation may vary based on several factors, including skills, experience, and education. Employees in this role will enjoy a comprehensive benefits package starting on day one of employment, including options for medical, dental, and vision insurance. Eligibility to enroll in the 401(k) retirement plan begins after 90 days of employment. Additionally, employees in this role will have access to paid sick leave and other paid time off benefits as required under the applicable law of the worksite location.

Nice to Have Skills & Experience

What Would Be Nice To Have:

• Experience supporting federal programs and/or data modernization projects.
• Experience delivering generative AI solutions using large language models (LLMs), retrieval-augmented generation, prompt engineering, vector databases, semantic search, AI agents, and model evaluation techniques.
• Experience with Azure AI services or comparable cloud AI platforms, containerization and orchestration, infrastructure automation, data pipelines, and federal security and compliance frameworks; familiarity with responsible AI, explainability, bias assessment, human-in-the-loop review, and model risk management is strongly preferred.
• Experience with Databricks, Snowflake, and other data processing or analytic technologies

Job Description

The Senior AI Developer / Technical Lead will lead the design, development, deployment, and delivery of complex artificial intelligence, machine learning, generative AI, and public health analytics solutions. This role combines hands-on technical leadership with end-to-end project oversight, translating program objectives into scalable AI architectures and actionable delivery plans. The position is responsible for guiding multidisciplinary teams, establishing secure and responsible AI development practices, managing technical risks, and ensuring high-quality, compliant solutions. The successful candidate will serve as a primary liaison between clients, product stakeholders, and technical teams while driving innovation, reproducibility, maintainability, and continuous improvement across AI and analytics workflows.

Key Responsibilities

• Lead end-to-end planning, architecture, development, testing, deployment, and delivery of complex AI, machine learning, generative AI, and public health analytics solutions, ensuring scope, schedule, budget, security, performance, and quality objectives are met.
• Translate client, user, and program objectives into technical requirements, AI solution architectures, product roadmaps, work plans, milestones, and deliverables aligned with federal standards, responsible AI principles, and stakeholder expectations.
• Provide hands-on technical leadership to multidisciplinary teams of AI developers, machine learning engineers, data engineers, data scientists, biostatisticians, and epidemiologists, fostering collaboration, accountability, code quality, and high performance.
• Serve as the primary technical point of contact for clients and stakeholders, communicating AI capabilities, limitations, tradeoffs, delivery status, and risks while facilitating timely technical and product decisions.
• Design and develop production-ready AI solutions, including machine learning models, generative AI applications, retrieval-augmented generation workflows, intelligent agents, APIs, and reusable software components using modern development frameworks and cloud services.
• Establish and oversee software engineering and MLOps practices, including version control, peer review, automated testing, CI/CD, model evaluation, monitoring, performance optimization, documentation, and secure deployment across development, test, and production environments.
• Evaluate emerging AI technologies and select appropriate models, frameworks, platforms, and integration patterns based on solution requirements, cost, scalability, security, explainability, and operational sustainability.
• Implement responsible AI, privacy, security, and data governance controls throughout the solution lifecycle; identify technical risks and dependencies; and mentor developers through architecture reviews, coding standards, troubleshooting, and knowledge sharing.