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# Agentic Delivery Software Engineer III

- **Company:** Deloitte T.T.L.
- **Location:** Westlake, TX, United States
- **Salary:** $107,600.0 - $198,400.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Code Generation, Information Systems, Cursor, DevOps, Systems Development Life Cycle, Software Engineering, Google Cloud, Cloud Platform System, GitHub Copilot, Multi-Agent Systems, Prompt Engineering, Agentic-AI, Containerization, Information Technology, Deployment Automation, Claude, Virtual Agents, Model Context Protocol
- **Published:** October 1, 2026
- **Apply:** https://dejobs.org/x/x/80519EB5E0F54FFBBACE33A050EA1EEE/job/

## About the Role

* Ability to work independently and collaborate as part of a team
 * Effective written and verbal communication skills
 * Meticulous attention to detail and quality of work product
 * Ability to build and sustain professional relationships
 * Ability to lead projects or workstreams
 * Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
 * Strong interpersonal skills and professional demeanor
 * Ability to meet deadlines
 * Ability to provide clear guidance to others, Required:
 * Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or a technical field
 * 4+ years of experience in software engineering or software development lifecycle (SDLC) delivery roles
 * 1+ years of experience reviewing code, tests, or technical deliverables for quality, completeness, and alignment to documented requirements
 * 1+ years of experience working in Agile delivery environments, including sprint execution, backlog refinement, and iterative delivery
 * 1+ years of experience using AI-assisted development tools such as Claude, GitHub Copilot, or Cursor
 * 1+ years of experience with prompt engineering, structured prompting, reusable context patterns, or prompt chaining
 * 1+ years of experience designing, developing, or implementing AI agents for software engineering, quality engineering, DevOps, or software delivery use cases
 * 1+ years of experience applying Agentic Development Lifecycle concepts such as task decomposition, context scoping, orchestration, validation controls, and human-in-the-loop review
 * Ability to travel 0-50%, on average, based on the work you do and the clients and industries/sectors you serve
 * Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

Preferred:

 * Experience with Model Context Protocol (MCP), tool integration patterns, or agent-to-system communication frameworks
 * Experience with multi-agent orchestration frameworks or coordination patterns supporting planning, execution, review, and escalation across specialized agents
 * Experience working with at least one cloud platform such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)
 * Experience with containerization, deployment automation, or platform engineering practices

## Description

As a Software Engineer III on the Customer team, you will advance AI-assisted software delivery, AI agent development, and agentic system implementation by helping teams translate requirements into structured workflows, validate outputs, and deliver scalable, high-quality technology solutions.

 * Break down business and technical requirements into structured tasks and context for agent-assisted delivery workflows
 * Execute and assign software development and agent development lifecycle activities across build, test, release, and validation
 * Collaborate with architecture, engineering, quality assurance, product, user experience, and technical documentation teams to support delivery consistency
 * Review agent-generated requirements, code, test assets, and technical documentation for quality, completeness, and alignment to requirements
 * Design, configure, and support AI agent implementations for software engineering use cases such as requirements analysis, code generation, test generation, release support, and technical documentation
 * Apply Agentic Development Lifecycle practices including task decomposition, context scoping, guardrails, validation checkpoints, and human-in-the-loop review to improve delivery reliability
 * Support implementation patterns for tool invocation, Model Context Protocol (MCP) integration, and multi-agent orchestration across specialized agent roles and delivery tasks
 * Lead other engineers in the use of secure, reliable, and scalable AI-assisted development practices, including agent-enabled workflows, prompt engineering, validation checkpoints, and governance of agent-generated outputs
 * Stay current on emerging best practices, industry-leading techniques, and evolving frameworks for AI agent development, deployment, orchestration, and governance