Applied AI Engineer
Deploy and operationalize AI agents within enterprise engineering organizations, integrating workflows, leading enablement, and measuring productivity impact. The role requires strong software engineering or technical consulting experience, coding proficiency, customer communication skills, and commercial judgment.
About the job
Responsibilities
- Embed with enterprise engineering teams to drive deep, lasting adoption of Devin, owning outcomes beyond onboarding.
- Architect and implement agentic workflows across engineering, QA, support, data, and product.
- Lead interactive programs for enterprise engineering teams, including live workshops and pair-programming sessions.
- Guide customers through installing, configuring, and optimizing Devin and associated tools such as DeepWiki and MCP integrations.
- Pair-program on live production problems to demonstrate high-value usage patterns and accelerate applied AI fluency.
- Quantify impact by tracking productivity metrics, surfacing ROI stories, and making the business case for expanding Devin's footprint within accounts.
- Turn field learnings into structured playbooks, best practices, digital learning content, and partner-driven enablement models.
- Create enablement materials and shared playbooks based on customer learnings.
Requirements
- Degree in a STEM field or equivalent hands-on experience.
- 3+ years as a software engineer, technical consultant, deployment strategist, forward deployed engineer, solutions engineer, or similar role with strong coding proficiency.
- Strong coding proficiency in Python, JavaScript/TypeScript, or similar languages.
- Ability to communicate complex technical topics to diverse audiences.
- Track record of driving technical adoption and measurable impact inside engineering organizations.
- Strong commercial instincts and understanding that successful engagements grow accounts.
- Excellent verbal and written communication skills.
- Ability to learn and adapt exceptionally fast.
Nice-to-haves
- Experience leading developer enablement, platform adoption, or internal AI modernization initiatives with measurable before-and-after results.
- Experience deploying or integrating LLM or agent-based systems in production.
- Experience founding or joining early-stage startups where autonomy and execution speed were critical.
- Enthusiasm for deliberately improving team velocity and scaling successful outcomes.
Skills
Python, JavaScript, TypeScript, LLMs, AI Agents, Mcp Integrations, Deepwiki, Pair Programming, Product Adoption, Productivity Metrics
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