AI Engineer

Robots & Pencils

. Build and ship AI/ML and LLM-powered system features for production .

Posted 9/29/2026full-timeRemote • United StatesMid-LevelSenior💰 $105,000 - $147,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying AI/ML systems, with a strong foundation in Python and experience in cloud platforms like AWS, GCP, or Azure. Proficient in data preprocessing, feature engineering, and integrating with APIs while adhering to responsible AI principles.

Highest-signal resume keywords

AI/ML Systems DevelopmentPython ProgrammingAWS, GCP, or AzureData Preprocessing and Feature EngineeringDocker and Kubernetes

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML SystemsGenerative AI DevelopmentPythonData IngestionModel DeploymentFeature EngineeringAPI IntegrationRAG PipelinesEvaluation PracticesAI Frameworks

Soft Skills

CollaborationOwnershipDocumentationCommunication

Tools & Technologies

DockerKubernetesClaude CodeCursor

Industry Keywords

AI SafetyResponsible AI PrinciplesPrompt Injection RisksPII HandlingToken Economics

Tech Stack

Tools & technologies

AWSAzureDockerGoogle Cloud PlatformKubernetesPython

About the role

Key responsibilities & impact

Build and ship AI/ML and LLM-powered system features for production
Implement and maintain AI/ML and AI agent pipeline components from data ingestion through model deployment
Contribute to LLM-powered features including prompts, evaluations, retrieval, and tool integrations
Handle data preprocessing, feature engineering, and basic evaluation to validate model and prompt performance
Collaborate with engineers across a distributed, cross-functional team
Document experiments, results, and model decisions
Participate in code reviews and team discussions
Take ownership of assigned tasks and deliver them end-to-end
Share experiment and research learnings with the broader team

Requirements

What you’ll need

3+ years of professional software engineering experience
Hands-on exposure to AI/ML systems and generative AI development
Solid software engineering foundation in Python or similar
Foundational knowledge of AWS, GCP, or Azure
Exposure to building or contributing to agentic AI systems
Familiarity with AI frameworks and orchestration tools
Familiarity with evaluation and observability practices for LLM applications
Awareness of AI safety, responsible AI principles, prompt injection risks, and PII handling
Exposure to RAG pipelines, including chunking strategies, embedding models, and vector databases
Experience building or integrating with internal and third-party APIs
Awareness of LLM cost considerations, including token economics and caching strategies
Working knowledge of Docker and exposure to Kubernetes
Demonstrable day-to-day usage of AI-forward coding tools such as Claude Code and Cursor

Benefits

Comp & perks

Paid time off
Medical insurance
Dental insurance
Vision insurance
401(k) for eligible employees