Senior AI Deployment & Platform Lead (Forward-Deployed)

Accenture; Seattle (WA); On-site; USD 141,000 - 337,000; Full time

Job summary

Accenture is hiring Forward Deployed AI Engineers to embed with client teams and scale AI-enabled workflows. You will own time-to-value, adoption, and reliability while delivering production-grade AI platforms and integrated solutions across complex enterprise environments. Travel 0–100% may be required.

Responsibilities include leading architecture design sessions, driving rapid experimentation, and shaping multi-year AI adoption roadmaps with executive stakeholders.

Qualifications

• 10+ years in engineering with cloud-native systems.
• 1+ year designing and deploying agentic solutions in production.
• 2+ years with AI platforms including multi-provider pipelines.
• 10+ years programming in Python/Java; observability skills.
• 10+ years production deployment experience (CI/CD, IaC).
• Strong client communication and ability to lead technical workshops.
• Bachelor's degree or equivalent work experience; AI certs are a plus.

Responsibilities

• Lead enterprise AI platform deployments across complex client environments.
• Own program-level delivery outcomes: time-to-value, reliability, adoption.
• Lead rapid experimentation turning problems into production systems.
• Architect and govern AI solutions across identity, data, security, governance.
• Shape reinvention strategy and publish reusable blueprints for clients.
• Lead architecture sessions, workshops, and code-with sessions with execs.
• Codify learnings and standards to grow the FDE practice.

Skills

Cloud-native systems

Agentic AI engineering

AI platforms experience

Python/Java

CI/CD pipelines

OpenAI / other models

Client workshops & leadership

Education

Bachelor's degree in Computer Science or Engineering

Tools

Terraform

Helm

Kubernetes

CI/CD tooling

Job description

Accenture is hiring Forward Deployed AI Engineers to embed with client teams and scale AI-enabled workflows. You will own time-to-value, adoption, and reliability while delivering production-grade AI platforms and integrated solutions across complex enterprise environments. Travel 0–100% may be required.

Responsibilities include leading architecture design sessions, driving rapid experimentation, and shaping multi-year AI adoption roadmaps with executive stakeholders.