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EPAM
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AI Solution Engineering Manager

EPAMMexico, Guadalajara
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Work model
Hybrid
Experience
7+ years
Employment
Not specified
Compensation
Not disclosed
Technology signal
15 tags

Technology context

15

Parsed from the vacancy text; ordered by relevance to this role.

AI AgentsAILLMFull StackAI-Assisted DevelopmentMachine LearningRAGBackendDevOpsFrontendCI/CDGitAI Agents FrameworksAI DIALAI Solution Engineering

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Role description

We are seeking an AI Solution Engineering Manager to improve how engineering teams build, test, and ship software by embedding AI into daily workflows, tooling, and pipelines. You will evaluate and integrate AI-assisted development approaches, measure impact on delivery, and coach teams on safe, effective adoption. Apply to help accelerate development outcomes.

Responsibilities

  • Assess current front-end and back-end engineering workflows to identify high-impact AI opportunities
  • Evaluate and deploy AI-assisted development tools across IDEs and developer environments
  • Design AI-driven automations for testing, documentation, and code review support
  • Integrate AI-based analysis and quality checks into CI/CD pipelines with DevOps partners
  • Create standards and guidelines for safe, ethical, and effective AI usage in engineering
  • Run workshops and training sessions to improve adoption of AI-assisted development practices
  • Measure and report productivity impact using delivery and engineering health metrics
  • Iterate on tooling configurations and prompts based on feedback from engineering teams

Requirements

  • 7+ years of experience with AI solution engineering or developer enablement initiatives
  • 7+ years of experience with AI & ML Strategy in software delivery contexts
  • Experience with AI Agents Frameworks applied to engineering workflows
  • Experience with AI DIAL for AI-assisted development enablement
  • Strong stakeholder management skills to guide teams through tooling and process change
  • Strong full-stack context across front-end frameworks and back-end systems
  • Solid IDE and developer tooling knowledge across editors, Git, and CI/CD systems
  • Strong analytical skills to define metrics and quantify productivity improvements
  • Strong communication and coaching skills to train engineers on AI-assisted practices
  • Upper-Intermediate English (B2) proficiency

Nice to have

  • Hands-on experience with LLM APIs and model providers used in engineering tooling
  • Experience with RAG pipelines, fine-tuning, or production-grade AI experimentation
  • Experience building internal developer platforms or DevEx tooling