AI Engineer

Mobile Mentor

AI Engineer designing and deploying production-grade AI agents and solutions for customers. Focused on full lifecycle management and customer enablement with hands-on engineering work.

Posted 5/23/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

About the role

Key responsibilities & impact

Design, build, test, deploy, and operate AI agents for customers using a combination of low-code and pro-code approaches
Develop customer-facing AI solutions across the full ALM lifecycle, including design, development, testing, deployment, and ongoing iteration
Build and integrate multi-model AI agents, selecting and orchestrating models based on use case, performance, and cost considerations
Design and implement Retrieval-Augmented Generation (RAG) solutions, including document ingestion, vector databases, indexing strategies, and retrieval logic
Configure and integrate MCP servers and related AI infrastructure components required for secure, scalable agent execution
Implement secure authentication and authorization patterns for AI agents, including identity, permissions, and service-to-service access
Collaborate with customers to understand business requirements and translate them into scalable AI agent designs
Apply sound engineering practices including version control, environment management, testing strategies, and deployment automation
Troubleshoot and optimize AI agents for performance, reliability, and accuracy
Partner closely with security, data, and adoption teams to ensure AI solutions are safe, compliant, and aligned with governance requirements
Translate the engineering work into customer enablement — designing and delivering technical training, workshops, labs, and demonstrations that help business users adopt the AI solutions you build
Deliver enablement sessions both virtually and on-site, adapting depth and language for executive, technical, and frontline audiences
Document architectures, designs, and operational considerations as part of customer deliverables and enablement assets

Requirements

What you’ll need

5+ years of experience in software engineering, application development, or AI/automation-focused engineering roles
Hands-on experience building AI agents or AI-powered applications using low-code and pro-code frameworks
Deep understanding of AI concepts and architectures, including model inference, orchestration, and agent design patterns
Practical experience with MCP servers, agent runtimes, or equivalent AI execution frameworks
Strong experience designing and implementing RAG architectures, including vector databases and retrieval pipelines
Experience working with multi-model AI approaches, including selecting, integrating, and managing multiple models within a single solution
Solid understanding of authentication, identity, and security controls in application and API design
Experience applying ALM best practices including source control, CI/CD, environment promotion, and testing
Ability to work directly with customers in solution design and delivery engagements
Strong verbal communication and public speaking skills with the ability to confidently lead live workshops, demos, and training sessions
Ability to translate complex or technical concepts into clear, practical learning experiences for non-technical audiences
Comfort traveling for work and delivering on-site engagements as part of customer projects
Strong problem-solving skills and comfort working in rapidly evolving technical domains.

Benefits

Comp & perks

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Hard Skills & Tools

AI agentslow-code frameworkspro-code frameworksRetrieval-Augmented Generation (RAG)vector databasesMCP serversmodel inferenceorchestrationCI/CDenvironment management

Soft Skills

verbal communicationpublic speakingproblem-solvingcustomer engagementtechnical trainingworkshop facilitationtranslating technical conceptscollaborationadaptabilityleadership