Lead AI Enablement Engineer

Matrix Global

. Drive adoption and evolution of AI-assisted engineering practices across product engineering teams .

Posted 10/12/2026full-timeNew York City • New York • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI-assisted engineering practices, including the development and integration of AI workflows, tools, and validation mechanisms. Proficient in software engineering fundamentals and capable of driving productivity and quality improvements through innovative AI solutions.

Highest-signal resume keywords

AI Coding ToolsLLM PlatformsCI/CD IntegrationPython ProgrammingAgent Orchestration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringApplication DevelopmentTestingCode ReviewDebuggingAI Coding AssistantsAgent InstructionsPrompt EngineeringReusable WorkflowsSecurity and Privacy

Soft Skills

CommunicationCollaborationCoaching

Tools & Technologies

Claude CodeWarpGitMCP ServersAWSContainersObservability ToolsIdentity and Access ManagementVector DatabasesSemantic Search

Industry Keywords

FintechPaymentsAccountingECommerceProperty ManagementTransactional BusinessesCompliance-Driven EnvironmentsRegulated Environments

Tech Stack

Tools & technologies

AWSCloudPythonTypeScriptGo.NET

About the role

Key responsibilities & impact

Drive adoption and evolution of AI-assisted engineering practices across product engineering teams
Establish and scale AI-assisted workflows across planning, coding, debugging, testing, design, documentation, code reviews, and production investigation
Develop reusable agent instructions, prompts, skills, repository context, integrations, and reference implementations
Evaluate AI coding tools, LLM platforms, and agent frameworks
Integrate AI workflows with CI/CD, automated testing, development sandboxes, observability, release readiness, and developer productivity tooling
Develop patterns for orchestrating multiple AI agents and parallel workflows with human oversight and validation
Build integrations with developer tools, repositories, APIs, and internal systems
Contribute to sandbox-based agent execution environments
Design validation loops, evaluation methods, and quality signals for AI-generated outputs
Apply engineering judgment to security, privacy, access control, auditability, operational risk, and AI usage costs
Define architectural patterns for AI-powered product features and internal employee capabilities
Support AI assistants, RAG solutions, knowledge agents, workflow automation, and tool-enabled applications
Drive adoption through demonstrations, pairing sessions, workshops, documentation, examples, and engineering office hours
Coach engineers on AI-assisted development, agent orchestration, and output validation
Measure and improve adoption, productivity, delivery speed, software quality, developer experience, and cost metrics

Requirements

What you’ll need

7+ years of software engineering experience preferred, with consideration for strong senior-level candidates who demonstrate exceptional hands-on AI engineering and enablement capabilities
Significant practical experience using AI tools for real-world software engineering, including AI coding assistants, agentic development workflows, and LLM-powered developer tools
Hands-on experience with Claude Code, Warp, or comparable AI coding and engineering platforms
Strong software engineering fundamentals, including application development, testing, code review, debugging, and production support
Experience building reusable developer workflows, integrations, automation, agent instructions, prompt patterns, skills, or reference implementations
Working knowledge of LLM APIs, tool calling, agent orchestration, and MCP or comparable integration approaches
Understanding of Git, CI/CD, automated testing, release management, and production readiness
Ability to evaluate AI-generated outputs and implement testing, review, security, and validation mechanisms
Proficiency in at least one modern programming language, such as Python, TypeScript, Go, C#, or .NET
Experience with several desirable technologies including agent SDKs/APIs, MCP servers, prompt engineering, RAG, semantic search, embeddings, vector databases, AWS or comparable cloud platforms, containers, observability, security controls, identity and access management, privacy, auditability, and governance
Strong communication and collaboration skills
Experience implementing sandboxed or cloud-based agent execution and parallel AI workflows is preferred
Familiarity with human-in-the-loop orchestration and validation is preferred
Experience building AI-powered SaaS features, knowledge-base agents, Slack integrations, or employee AI assistants is preferred
Domain experience in fintech, payments, accounting, eCommerce, property management, or transactional businesses is preferred
Experience in security-conscious, compliance-driven, or regulated environments is preferred

Benefits

Comp & perks

Competitive compensation and benefits
Meaningful career development opportunities
Flexible work arrangements
In-person collaboration and remote-friendly work options
Diverse, inclusive culture
Continuous learning and growth