AI Development Lead
About The Position
We are seeking a AI Development Lead to drive the design, development, and delivery of AI solutions, especially Generative AI, for clients modernizing their operations through intelligent automation. This hands-on leader will guide agile teams in developing AI-enabled Minimum Viable Products (MVPs) while advising on architecture, deployment, and governance strategies. The ideal candidate blends strong technical depth in modern AI tools with consulting experience, ensuring that emerging technologies deliver measurable value for clients. AI Delivery Leadership Lead the end-to-end delivery of AI MVPs, from use case definition through demonstration and iteration, including engaging directly with clients. Design solution architectures and technical roadmaps that integrate AI components within client cloud environments. Oversee model development, validation, and user interface integration to create functional prototypes. Deliver MVP demonstrations, gather stakeholder feedback, and refine solutions through post-deployment feedback loops. Construct and maintain scalable data pipelines for processing, transforming, and feeding data into AI models and applications. Agile Development & Team Enablement Lead agile development sprints and facilitate SCRUM ceremonies to ensure quality, velocity, and stakeholder alignment. Mentor developers and data scientists, fostering collaboration and excellence in applied AI engineering. Support backlog management, sprint prioritization, and delivery tracking across multidisciplinary teams. Generative AI & Technical Advisory Apply Generative AI and Large Language Model (LLM) techniques to automate, analyze, and enhance compliance and operational workflows. Evaluate and refine prompt engineering and context enrichment strategies for AI-based applications. Assess and optimize existing AI toolchains and workflows to improve scalability and delivery efficiency. Advise on production deployment strategies, including security, performance, and data integration considerations. Conduct operational readiness assessments to evaluate solution performance, resilience, and maintainability. Design lightweight model monitoring and retraining pipelines to maintain relevance and accuracy. Support AI governance alignment, ensuring all solutions adhere to organizational standards and risk management practices. Serve as the primary client interface for technical leadership, solution assurance, and delivery success. Construct and maintain scalable data pipelines for processing, transforming, and feeding data into AI models and applications. Collaborate with cross-functional teams to rapidly prototype and iterate on solutions Deploy and manage applications and models in cloud environments leveraging infrastructure-as-code and DevOps best practices.
Requirements
- Bachelor’s degree is required
- Minimum SEVEN (7) years of experience delivering AI, software, or data-driven solutions
- Minimum TWO (2) years in a leadership or client-facing consulting role
- Hands-on experience designing or implementing Generative AI systems (e.g., knowledge assistants, automation workflows, or retrieval-based reasoning) in cloud environments (e.g. Azure, Amazon Web Services)
- Experience with key Generative AI system patterns, such as: RAG (Retrieval-Augmented Generation) and retrieval-based reasoning systems Agentic frameworks (e.g., orchestrated multi-step reasoning, tool-using AI agents) Evaluation and observability frameworks (e.g., LLM/human evals, prompt testing, reliability scoring) Model monitoring and retraining pipelines
- Proficiency in Python and experience developing applications or pipelines that integrate AI/LLMs via APIs or SDKs (e.g. LangChain, LangGraph or similar)
- Strong understanding of AI architecture, data integration, and model lifecycle management
- Demonstrated experience leading teams using Agile and DevOps delivery practices, including sprint management, CI/CD, and iterative prototyping
- Excellent communication, stakeholder engagement, and problem-solving skills
Nice To Haves
- Master’s degree
- Experience designing or deploying solutions with Amazon Bedrock, SageMaker, or other AWS AI services
- Understanding of AI governance and risk management frameworks
- Experience supporting clients in regulated or complex environments (e.g., energy, infrastructure, public sector)
Responsibilities
- Lead the end-to-end delivery of AI MVPs, from use case definition through demonstration and iteration, including engaging directly with clients.
- Design solution architectures and technical roadmaps that integrate AI components within client cloud environments.
- Oversee model development, validation, and user interface integration to create functional prototypes.
- Deliver MVP demonstrations, gather stakeholder feedback, and refine solutions through post-deployment feedback loops.
- Construct and maintain scalable data pipelines for processing, transforming, and feeding data into AI models and applications.
- Lead agile development sprints and facilitate SCRUM ceremonies to ensure quality, velocity, and stakeholder alignment.
- Mentor developers and data scientists, fostering collaboration and excellence in applied AI engineering.
- Support backlog management, sprint prioritization, and delivery tracking across multidisciplinary teams.
- Apply Generative AI and Large Language Model (LLM) techniques to automate, analyze, and enhance compliance and operational workflows.
- Evaluate and refine prompt engineering and context enrichment strategies for AI-based applications.
- Assess and optimize existing AI toolchains and workflows to improve scalability and delivery efficiency.
- Advise on production deployment strategies, including security, performance, and data integration considerations.
- Conduct operational readiness assessments to evaluate solution performance, resilience, and maintainability.
- Design lightweight model monitoring and retraining pipelines to maintain relevance and accuracy.
- Support AI governance alignment, ensuring all solutions adhere to organizational standards and risk management practices.
- Serve as the primary client interface for technical leadership, solution assurance, and delivery success.
- Construct and maintain scalable data pipelines for processing, transforming, and feeding data into AI models and applications.
- Collaborate with cross-functional teams to rapidly prototype and iterate on solutions
- Deploy and manage applications and models in cloud environments leveraging infrastructure-as-code and DevOps best practices.
Benefits
- Medical, Rx, Dental & Vision Insurance
- Personal and Family Sick Time & Company Paid Holidays
- Position may be eligible for a discretionary variable incentive bonus
- Parental Leave and Adoption Assistance
- 401(k) Retirement Plan
- Basic Life & Supplemental Life
- Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
- Short-Term & Long-Term Disability
- Student Loan PayDown
- Tuition Reimbursement, Personal Development & Learning Opportunities
- Skills Development & Certifications
- Employee Referral Program
- Corporate Sponsored Events & Community Outreach
- Emergency Back-Up Childcare Program
- Mobility Stipend
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
