AI/ML Technical Architect Lead

Accountabilities

• • Lead AI/ML strategy, solution architecture, technical implementation, and modernization initiatives across complex programs.
  • Design, develop, integrate, and deploy scalable AI/ML models and intelligent systems supporting decision-making, automation, productivity, and operational readiness.
  • Lead the development of predictive analytics capabilities, automation frameworks, and intelligent decision-support solutions.
  • Provide hands-on technical leadership throughout the AI/ML development lifecycle, from experimentation and prototyping through production deployment and ongoing optimization.
  • Oversee data engineering pipelines, MLOps processes, model lifecycle management, validation, monitoring, explainability, and bias mitigation.
  • Integrate AI/ML capabilities into secure enterprise and restricted environments while incorporating cybersecurity, data governance, ethical AI, and compliance requirements into development workflows.
  • Support security risk management activities, including threat assessments, authorization documentation, configuration management, incident response documentation, audits, and governance reviews.
  • Ensure AI/ML solutions align with applicable risk management and cybersecurity frameworks and maintain continuous compliance.
  • Collaborate with security teams, business owners, technical stakeholders, and program leadership to deliver secure and effective AI solutions.
  • Advise leadership on emerging AI technologies, practical mission applications, modernization opportunities, and responsible AI practices.
  • Help transition experimental and prototype AI capabilities into reliable, scalable production systems.
  • Mentor junior engineers and provide technical guidance across multidisciplinary teams.

  Requirements

  • Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical discipline; a Master’s degree or PhD is preferred.
  • 10+ years of progressive experience in AI/ML, data science, software engineering, advanced analytics, or a closely related field, including substantial hands-on experience with modern AI technologies.
  • At least 5 years of hands-on experience designing, developing, and deploying AI/ML solutions in production environments, including experience with MLOps practices.
  • Demonstrated ability to personally develop AI/ML solutions rather than focusing exclusively on architecture or management.
  • Strong programming skills in Python, R, Java, or comparable languages.
  • Deep knowledge of machine learning frameworks such as TensorFlow or PyTorch, ideally with implementation experience using AWS SageMaker.
  • Experience integrating AI/ML solutions into secure enterprise environments and working within cybersecurity, data governance, regulatory, and compliance requirements.
  • Practical experience building AI products or functional prototypes using Retrieval-Augmented Generation (RAG) and agentic AI technologies.
  • Experience with cloud platforms, preferably AWS, with Azure or Google Cloud experience also considered.
  • Familiarity with AI services such as AWS Bedrock, Azure AI Foundry, or Google Vertex AI.
  • Experience implementing AI solutions in secure, restricted, regulated, or highly governed environments.
  • Ability to obtain Public Trust clearance and meet applicable background eligibility requirements.
  • Must have lived in the United States for at least 3 of the last 5 years.
  • Experience with enterprise-scale Salesforce solutions is preferred, particularly Agentforce implementations.
  • Familiarity with AI governance, responsible AI, modernization programs, and enterprise transformation initiatives is advantageous.
  • Experience supporting U.S. federal agencies, particularly healthcare or public-sector organizations, is preferred.
  • Experience with AWS GovCloud, Azure Government, Zero Trust architectures, or comparable secure-cloud environments is a strong advantage.
  • Strong communication, stakeholder management, problem-solving, mentoring, and technical leadership skills.

  Benefits

  • Estimated salary range of $204,000–$276,000, with actual compensation determined by experience, geographic location, and applicable contractual considerations.
  • Comprehensive medical plan options, including plans with Health Savings Accounts.
  • Dental and vision insurance options.
  • 401(k) plan with company matching and pre-tax and post-tax contribution options.
  • Paid time off, including vacation, sick, personal, holiday, parental, military, bereavement, and jury-duty leave.
  • Typically 15 days of paid leave per calendar year for vacation, personal business, and illness, plus 10 paid holidays.
  • Paid family leave of up to 160 hours within a rolling 12-month period for eligible employees.
  • Short- and long-term disability coverage, life insurance, accidental death and dismemberment coverage, and other insurance options.
  • Flexible work arrangements designed to support work-life balance.
  • Career development resources, including AI-powered career planning and learning opportunities.
  • Internal mobility support to help employees pursue long-term career goals.
  • Opportunities to work with advanced AI, cloud, cybersecurity, and software technologies on complex, high-impact initiatives.
  • Collaborative environment with opportunities to mentor others and influence technical strategy.
  • Full-time schedule of 40 hours per week, with limited travel of less than 10%.