AI Development Lead
Job in
Arlington, Arlington County, Virginia, 22201, USA
Listed on 2025-12-30
Listing for:
Guidehouse
Full Time
position Listed on 2025-12-30
Job specializations:
-
IT/Tech
AI Engineer, Data Science Manager, Machine Learning/ ML Engineer
Job Description & How to Apply Below
What You Will Do
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.
AIDelivery 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.
- 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 tool chains 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 Dev Ops best practices.
- 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. Lang Chain, Lang Graph or similar)
- Strong understanding of AI architecture, data integration, and model lifecycle management
- Demonstrated experience leading teams using Agile and Dev Ops delivery practices, including sprint management, CI/CD, and iterative prototyping
- Excellent communication, stakeholder engagement, and problem‑solving skills
- Master’s degree
- Experience designing or deploying solutions with Amazon Bedrock, Sage Maker, or other AWS AI services
- Under…
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