AI-Native SDLC Transformation Lead

Accenture; San Francisco (CA); On-site; USD 94,000 - 266,000; Full time

Job summary

Accenture in the United States is seeking an AI SDLC Transformation Manager to guide enterprise software delivery toward AI-native workflows. You will surface waste with flow metrics, design future-state processes, and build agentic systems across upstream SDLC phases using multi-agent and LLM-enabled approaches.

You will collaborate with product, engineering, QA, security and platform teams, translating evolving AI tooling into actionable roadmaps for large clients. Travel may be required.

Qualifications

• Minimum of 5 years working across the full SDLC, requirements through release, with demonstrated ability to map, measure, and redesign delivery processes.
• Minimum of 3 years of hands-on experience designing or building multi-agent or LLM-integrated systems, including prompt engineering, tool-use orchestration, or agentic application development.
• Minimum of 3 years in a consulting or advisory capacity working with engineering organizations, ideally at enterprise scale (5,000+ employees or $1B+ revenue).
• Minimum of 3 years applying flow metrics (cycle time, WIP, throughput, flow efficiency) or value stream mapping as active diagnostic tools, not just frameworks you've presented on.
• Minimum of 2 years working directly with AI/ML systems, LLMs, or agentic architectures in a professional context.
• Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)

Responsibilities

• Value stream mapping and flow metric analysis (cycle time, flow efficiency, WIP, throughput) to identify waste in existing SDLC practices
• Design of AI-native to-be processes that restructure and accelerate how software is defined, designed, and governed
• Change management for engineering teams transitioning to AI-augmented workflows
• Strategy and design of agentic systems targeting upstream SDLC phases: requirements generation, user story synthesis, design review, and architecture validation
• Know how and where to use creator and reviewer agent patterns and the token impact of doing so.
• Model SDLC as a system, identifying feedback loops, bottlenecks, and second-order effects of process changes
• Cross-functional perspective spanning product, engineering, QA, security, and platform
• Ability to maintain fluency in the rapidly evolving AI tooling ecosystem (coding assistants, agentic platforms, evaluation frameworks, MCP/tool orchestration)
• Ongoing research practice tracking capability shifts, new model releases, and emerging practitioner patterns
• Expertise in what digitally native organizations are doing today and ability to translate those benchmarks into actionable roadmaps for enterprise clients
• Ability to influence clients to change and modernize processes that limit the positive impact of agentic ways of working and overall SDLC

Skills

SDLC experience

Multi-agent/LLM systems

Consulting experience

Flow metrics

AI/ML systems

Bachelor's degree

Education

Bachelor's degree

Job description

Accenture in the United States is seeking an AI SDLC Transformation Manager to guide enterprise software delivery toward AI-native workflows. You will surface waste with flow metrics, design future-state processes, and build agentic systems across upstream SDLC phases using multi-agent and LLM-enabled approaches.

You will collaborate with product, engineering, QA, security and platform teams, translating evolving AI tooling into actionable roadmaps for large clients. Travel may be required.