Senior AI Engineer

Robots & Pencils

. Design, implement, and deploy ML/AI models end-to-end, from concept through production, including data pipelines, training workflows, and optimization for performance, accuracy, and efficiency .

Posted 10/15/2026full-timeRemote • ColombiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, implementing, and deploying AI/ML models, with a strong focus on performance optimization and production reliability. Proficient in collaborating with cross-functional teams to align AI initiatives with business objectives while ensuring adherence to responsible AI principles.

Highest-signal resume keywords

AI/ML Systems DevelopmentPython ProgrammingAWS Services KnowledgeGenerative AI DevelopmentAPI Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningArtificial IntelligenceData Pipeline DesignModel OptimizationAI FrameworksEvaluation FrameworksRAG Pipeline BuildingCost OptimizationContainerization with DockerKubernetes

Soft Skills

Problem-SolvingCollaborationConstructive Feedback

Tools & Technologies

Claude CodeCursorObservability ToolsOrchestration ToolsVector Databases

Industry Keywords

AI SafetyResponsible AI PrinciplesPrompt Injection DefensesPII Handling

Tech Stack

Tools & technologies

AWSCloudDockerKubernetesPython

About the role

Key responsibilities & impact

Design, implement, and deploy ML/AI models end-to-end, from concept through production, including data pipelines, training workflows, and optimization for performance, accuracy, and efficiency
Maintain and evolve AI systems in production, monitoring for drift, debugging issues, and driving ongoing improvements to reliability and scalability
Use AI-forward coding tools such as Claude and Cursor to ship higher-quality work at pace
Partner with product, engineering, and data teams to align AI work with broader product and business goals
Translate technical tradeoffs, model behavior, and constraints into terms non-specialists can act on
Participate actively in code reviews and design discussions, raising concerns and offering constructive feedback
Contribute to AI architecture decisions with perspective on tradeoffs and long-term implications
Take ownership of meaningful work end-to-end, including getting AI into production
Raise engineering practices through individual contributions and by supporting more junior engineers

Requirements

What you’ll need

4+ years professional software engineering experience, with 2+ years focused on AI/ML systems in production and hands-on experience with generative AI development
Strong software engineering background (Python or similar)
Working knowledge of cloud platforms, preferably with in-depth understanding of AWS services and AWS GenAI offerings
Proven ability to design and ship agentic systems
Experience with AI frameworks and orchestration tools
Experience with evaluation frameworks and observability tools for LLM apps
Understanding of AI safety, responsible AI principles, prompt injection defenses, and PII handling
Hands-on experience building RAG pipelines: chunking strategies, embedding models, vector databases
API development experience, including designing and integrating with internal and third-party services
Cost optimization expertise: token economics, caching strategies, model routing, quantization
Working knowledge of Docker and Kubernetes for containerized deployments
Demonstrable, day-to-day usage and knowledge of AI-forward coding tools such as Claude Code and Cursor
Strong problem-solving skills and ability to navigate ambiguous technical challenges with sound judgment

Benefits

Comp & perks

Specialized training through the Advanced AWS Partnership and AWS Patterns Partnership
Early access to emerging cloud capabilities
Access to advanced engineering resources
Accelerated professional growth
Hands-on exposure to complex problem-solving
Collaboration with experienced architects and senior engineers
Work within an elite global engineering ecosystem