Forward Deployed AI Engineer

Keyrus

Forward Deployed AI Engineer building production GenAI and agentic AI solutions for Keyrus. Delivering measurable digital and data transformation outcomes for global customers.

Posted 8/18/2026full-timeRemote • 🇨🇴 ColombiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in delivering AI and GenAI solutions, with strong capabilities in Python development, API integration, and cloud platforms. Proven ability to collaborate with diverse stakeholders and translate complex use cases into measurable, production-ready solutions.

Highest-signal resume keywords

AI EngineeringPython DevelopmentGenAI ArchitecturesAPI IntegrationCloud Platform Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI EngineeringMachine LearningSoftware EngineeringData EngineeringPython DevelopmentAPI IntegrationLarge Language ModelsRAG ArchitecturesMLOps/LLMOpsProduction Deployment

Soft Skills

CollaborationStakeholder ManagementProblem SolvingAdaptabilityCommunication

Tools & Technologies

LangChainLlamaIndexLangGraphSemantic KernelAutoGenDockerGitCI/CDMonitoring ToolsEvaluation Tools

Industry Keywords

Digital ProjectsData ProjectsGovernanceData PrivacyResponsible AI

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Co-create solutions with business and technical stakeholders through workshops, rapid iterations, and hands-on delivery
Locate, qualify, and secure access to data required for each use case, working directly with the Data Engineer
Translate use cases into production-ready GenAI and agentic AI solutions, including RAG architectures, intelligent assistants, and AI-enabled workflows
Prototype, test, deploy, monitor, and improve solutions in real client environments using user and domain-expert feedback
Collaborate with Data Engineers, Software Engineers, Foundations Architects, Governance experts, Business Value Advisors, and Service Delivery Managers
Balance speed, quality, cost, security, and maintainability through clear technical and delivery trade-offs
Define success criteria covering adoption, performance, reliability, risk, cost, and measurable business value
Ensure solutions are documented, governed, and transferable for client operation
Turn successful delivery into reusable patterns, accelerators, and building blocks for future engagements
Work with global customers on innovative Digital & Data projects

Requirements

What you’ll need

Typically 5–10 years of relevant experience in AI Engineering, Machine Learning, Software Engineering, Data Engineering, or technical consulting
Hands-on experience delivering AI, GenAI, or software solutions into production
Experience working directly with clients or in complex stakeholder environments
Evidence of turning complex use cases into adopted, measurable solutions
A degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience
Strong Python development skills
API integration experience and modern software-engineering practices
Hands-on experience with Large Language Models, GenAI architectures, prompt workflows, and model/provider selection
Experience with RAG, embeddings, vector search, AI agents, and agentic workflows
Familiarity with LangChain, LlamaIndex, LangGraph, Semantic Kernel, AutoGen, or comparable tools
Experience integrating AI into enterprise systems, APIs, and business workflows
Experience with at least one major cloud platform: Azure, AWS, or GCP
Working knowledge of Docker, Git, CI/CD, production deployment, monitoring, and evaluation
Understanding of MLOps/LLMOps, security, data privacy, governance, and responsible AI principles

Benefits

Comp & perks

100% remote work
International and multicultural projects
Access to training programs and continuous professional development
Professional growth opportunities and internal mobility
A culture built on collaboration, innovation, and continuous learning
Diversity and multicultural work environment