Enterprise AI Engineer — Deploy & Scale AI Workflows

Fdetimes

Sydney

Hybrid

AUD 140,000 - 200,000

Full time

14 days+

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Job summary

Cognition is hiring an Applied AI Engineer to embed with enterprise teams and drive adoption of Devin, our AI software engineer. You’ll architect workflows, run live workshops, and guide customers from installation to optimization, building repeatable playbooks and enabling scalable success.

You’ll be working with clients to quantify productivity gains, articulate ROI, and scale learnings across hundreds of teams while maintaining strong engineering fundamentals and customer focus.

Qualifications

  • Degree in a STEM field or equivalent hands-on experience.
  • 3+ years as a software engineer or related roles with strong coding proficiency.
  • Ability to communicate complex technical topics to diverse audiences.
  • Proven track record of driving technical adoption and measurable impact.

Responsibilities

  • Embed with enterprise engineering teams to drive adoption of Devin.
  • Architect and implement agentic workflows across engineering, QA, support, data, and product.
  • Lead interactive programs for enterprise teams (workshops, pair programming).
  • Guide customers through installing, configuring, and optimizing Devin and its tools.
  • Pair-program on live production problems to demonstrate high-value usage patterns.
  • Quantify impact with productivity metrics and ROI stories.
  • Scale field learnings into structured playbooks and best practices.
  • Create enablement materials and shared playbooks.

Skills

Coding proficiency
Communication skills
Adoption focus

Education

Degree in STEM

Job description

Cognition is hiring an Applied AI Engineer to embed with enterprise teams and drive adoption of Devin, our AI software engineer. You’ll architect workflows, run live workshops, and guide customers from installation to optimization, building repeatable playbooks and enabling scalable success.

You’ll be working with clients to quantify productivity gains, articulate ROI, and scale learnings across hundreds of teams while maintaining strong engineering fundamentals and customer focus.

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