AI Solution Engineering Manager

EPAM Systems; Mexico; On-site; PHP 7,384,615 - 11,076,922; Full time

Job summary

EPAM Systems is seeking an AI Solution Engineering Manager to advance how engineering teams build, test, and ship software by embedding AI into workflows, tooling, and pipelines. You will evaluate AI-assisted development approaches, measure impact on delivery, and coach teams on safe adoption.

The role requires deep experience in AI/ML strategy, AI agents frameworks, and strong leadership to drive DevOps-aligned AI solutions across front-end and back-end stacks. English at B2 level is essential.

Qualifications

• 7+ years of AI solution engineering or developer enablement initiatives.
• 7+ years of 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.

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.

Skills

AI/ML strategy

Frontend & Backend

DevOps & CI/CD

Stakeholder management

Communication coaching

English B2

Tools

IDE tooling

Git

CI/CD tooling

Job 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.

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