AI Engineer

Robots & Pencils

. Build and ship AI/ML and LLM-powered system features with guidance from senior engineers .

Posted 10/8/2026full-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 cloud platforms like AWS. Capable of handling data preprocessing, feature engineering, and ensuring responsible AI practices while collaborating effectively in cross-functional teams.

Highest-signal resume keywords

AI/ML System DevelopmentPython ProgrammingAWS Cloud ExpertiseData PreprocessingDocker and Kubernetes

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML SystemsGenerative AI DevelopmentData IngestionModel DeploymentFeature EngineeringEvaluation PracticesRAG PipelinesAPI IntegrationToken EconomicsAI Frameworks

Soft Skills

OwnershipCollaborationDocumentationCommunicationTeam Participation

Tools & Technologies

AWSGCPAzureDockerKubernetesClaude CodeCursor

Industry Keywords

AI SafetyResponsible AI PrinciplesPrompt Injection RisksPII HandlingObservability Practices

Tech Stack

Tools & technologies

AWSAzureDockerGoogle Cloud PlatformKubernetesPython

About the role

Key responsibilities & impact

Build and ship AI/ML and LLM-powered system features with guidance from senior engineers
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 prepare quality inputs and validate model and prompt performance
Work closely 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
Build and support production-ready AI systems for enterprise operations and client workflows

Requirements

What you’ll need

3+ years of professional software engineering experience with hands-on exposure to AI/ML systems and generative AI development
Solid software engineering foundation, including Python or similar
Foundational knowledge of AWS, GCP, or Azure; interest in deepening AWS and AWS GenAI expertise
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
Ability to work effectively in a distributed, cross-functional team
Ability to take ownership of assigned tasks and deliver end-to-end
Ability to document experiments, results, and model decisions clearly
Ability to participate in code reviews and team discussions

Benefits

Comp & perks

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