Agentic Delivery Senior Engineer
- Lead the decomposition of business and technical requirements into structured workflows, prompts, tasks, and checkpoints for multi-agent SDLC delivery
- Coordinate end-to-end execution across architecture, engineering, QA, UX, product, and technical writing contributors to maintain cross-agent and cross-team consistency
- Drive quality and delivery outcomes across requirements, code, testing, compliance, and release readiness
- Review and validate agent-generated outputs using human-in-the-loop quality checkpoints and technical judgment
- Lead issue resolution across upstream and downstream delivery dependencies, including integration, testing, and production-readiness concerns
- Establish and reinforce standards for code quality, technical documentation, testing rigor, and delivery governance in AI-assisted workflows
- Coach junior practitioners in prompt engineering, engineering quality, delivery methods, and technical review practices
- Identify and implement process improvements that increase delivery speed, quality, repeatability, or control across agent-enabled engineering workflows
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or a related technical field
- 4+ years of experience in software engineering, architecture, quality engineering, DevOps, SRE, or related SDLC delivery roles
- 1+ years of experience delivering production, operational, or client-facing technology solutions in complex delivery environments
- 1+ years of experience translating business requirements into technical designs, delivery plans, and execution checkpoints across multiple stakeholders
- 1+ years of experience using AI-assisted development tools such as Claude, GitHub Copilot, Cursor, or similar tools in professional or project settings
- 1+ years of experience reviewing and validating work produced by others, including code reviews, design reviews, test reviews, or release-readiness reviews
- 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 0-50%, 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 one or more modern engineering or data platforms such as Databricks, Snowflake, Airflow, dbt, Kubernetes, or comparable tools
- Experience applying at least two MLOps or AI delivery practices such as deployment pipelines, monitoring, experiment tracking, model governance, or containerization
- Experience with prompt engineering, LLM APIs, orchestration patterns, or retrieval-augmented generation architectures
- Experience using BI, reporting, or visualization tools to support adoption, operational visibility, or business insight generation
- Experience coaching junior team members and reviewing technical deliverables for quality, accuracy, and completeness
- Familiarity with responsible AI practices, including transparency, bias considerations, governance, and human oversight controls
- Experience with Agile delivery practices, including sprint planning, backlog management, dependency coordination, and stakeholder communication
- Strong written and verbal communication skills with the ability to explain technical trade-offs, risks, and delivery status to varied audiences
- Government consulting experience
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