Lead Agentic Delivery Engineer
- Lead the design, implementation, deployment, and support of AI/ML, analytics, automation, and generative AI solutions for client programs
- Translate business and functional requirements into technical plans, solution components, and production-ready workflows
- Oversee the development of data pipelines, model integration, validation processes, and other scalable technical assets
- Manage delivery workstreams and guide teams in using Python, SQL, cloud platforms, and modern data tools to solve business problems
- Define and monitor KPIs related to solution quality, model performance, data health, adoption, and business impact
- Mentor junior practitioners and partner with client and internal stakeholders to drive execution, communicate progress and risks, and promote responsible, repeatable delivery practices
- Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, Mathematics, Information Systems, or a related technical field
- 5+ years of experience in one or more of the following: software engineering, analytics, AI/ML, data, automation, or technology implementation
- 5+ years of experience translating business requirements into technical designs, build activities, or deployment plans and integrating technical solutions into business processes, applications, or user workflows across technical stakeholders
- 2+ years of experience delivering AI/ML, data, automation, and generative AI solutions in production, operational, or client-facing environments, including prompt engineering, LLM APIs, orchestration, and RAG architectures
- 2+ years of experience using Python and SQL and working in cloud or modern data environments
- Experience leading at least one workstream, team, or end-to-end solution component from requirements through implementation
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
- Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve
- Experience working with at least one major cloud platform, such as AWS, Azure, or GCP
- Experience using at least one or more modern data engineering tools, such as Databricks, Snowflake, BigQuery, dbt, Airflow, or comparable platforms
- Experience applying at least two MLOps practices, such as deployment pipelines, monitoring, experiment tracking, model governance, or containerization
- Experience using at least one BI or visualization tool to support solution adoption, reporting, or business insight generation
- Experience coaching junior team members and reviewing technical deliverables for quality, accuracy, or completeness
- Familiarity with responsible AI practices, including model transparency, bias considerations, and governance processes
- Government consulting experience
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