AI SDLC Transformation Lead

Information Technology Senior Management Forum; Boston (MA); On-site; USD 94,000 - 245,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) plan

Bonus opportunities

Job summary

Accenture is seeking an AI SDLC Transformation Manager to guide enterprise clients in redesigning software delivery to be AI-native. You will map and optimize flow, design future-state AI-native workflows, and lead multi-agent initiatives across enterprise engineering teams.

Travel may be required; compensation varies by location and experience, with an emphasis on delivering scalable AI-enabled delivery models for large clients.

Qualifications

• Minimum of 5 years across the full SDLC, requirements through release.
• Minimum of 3 years designing or building multi-agent or LLM-integrated systems.
• Minimum of 3 years in a consulting/advisory capacity with enterprise-scale engineering teams.
• Minimum of 3 years applying flow metrics like cycle time, WIP, throughput as diagnostic tools.
• Minimum of 2 years working directly with AI/ML systems, LLMs, or agentic architectures.

Responsibilities

• Value stream mapping and flow metric analysis to identify waste in existing SDLC practices.
• Design future-state AI-native workflows and agentic systems for upstream SDLC phases.
• Change management for engineering teams transitioning to AI-augmented workflows.
• Strategize and design agentic systems targeting upstream SDLC phases: requirements generation, user stories, design reviews.

Skills

Flow metric analysis

Multi-agent systems

AI tooling fluency

Change management

Strategy design

Education

Bachelor's degree or equivalent

Tools

GitHub Copilot

Cursor

Amazon Q Developer

Cody

Job description

Accenture is seeking an AI SDLC Transformation Manager to guide enterprise clients in redesigning software delivery to be AI-native. You will map and optimize flow, design future-state AI-native workflows, and lead multi-agent initiatives across enterprise engineering teams.

Travel may be required; compensation varies by location and experience, with an emphasis on delivering scalable AI-enabled delivery models for large clients.