Senior Data Engineer — Remote AWS AI/ML Platform

Robots and Pencils; United States; Remote; USD 120,000 - 165,000; Full time

Job summary

Robots & Pencils is seeking a Senior Data Engineer to design, build, and deliver the data and AI infrastructure behind an enterprise AI platform. You will work with AWS Services and cross-functional teams on a scaling observability data platform, from an initial pilot to full automation, focusing on data pipelines, instrumentations, and agent-enablement tooling.

The role emphasizes reliability, security, and scalability, with collaboration among senior engineers to shape architecture and

Qualifications

• 5+ years professional software or data engineering experience, with 2+ years building data platforms or AI/ML systems in production on AWS
• Strong software engineering background (Python and SQL, or similar)
• AWS Certified Data Engineer – Associate. Candidates without it are considered if there is a clear, near-term path to earning it
• Hands-on experience building data lakes on AWS, including S3, Lake Formation, Glue, Athena, and Iceberg or Parquet, with exposure to streaming on Kinesis or MSK
• Experience with observability for distributed and AI systems, including CloudWatch, X-Ray, OpenTelemetry/ADOT, Amazon Managed Service for Prometheus and Grafana, and drift monitoring with SageMaker Model Monitor
• Working knowledge of agent enablement on AWS, including Amazon Bedrock Knowledge Bases, Guardrails, RAG patterns, and Bedrock Agents
• Experience shipping agentic or ML systems in production environments
• Experience with MLOps and LLMOps practices, including evaluation, deployment, and monitoring of models and agents
• Experience with infrastructure as code using AWS CDK, and CI/CD for data and AI systems
• Understanding of IAM and KMS security, data governance, responsible AI principles, and PII handling
• Cost optimization experience across storage, query, compute, and model usage
• Experience delivering solutions in a consulting or professional services setting, working alongside client and partner teams
• Demonstrable, day-to-day usage and knowledge of AI-forward coding tools such as Claude Code and Cursor
• Strong problem-solving skills and the ability to navigate ambiguous technical challenges with sound judgment

Responsibilities

• Design, implement, and deploy data and AI/ML systems on AWS end-to-end, from concept through production, including data lake pipelines, observability instrumentation, and optimization for performance, reliability, and cost
• Maintain and evolve platforms in production, monitoring for drift, debugging issues, and driving ongoing improvements to reliability and scalability
• Bring an AI-forward coding mindset to your daily work, using tools like Claude and Cursor to ship higher-quality work at pace
• Partner closely with AWS Professional Services, client engineering, and data teams to align the work with broader platform and business goals
• Translate technical tradeoffs, system 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 data and AI architecture decisions with thoughtful perspective on tradeoffs and long-term implications
• Take ownership of meaningful work end-to-end, including the unglamorous parts of getting AI into production
• Raise the bar on engineering practices through your own work and by supporting more junior engineers when opportunities arise

Skills

AWS

Python

SQL

Data pipelines

Observability

MLOps

CI/CD

IAM/KMS security

Bedrock Agents

Claude/Cursor tools

Tools

AWS CDK

CloudWatch

X-Ray

OpenTelemetry

Grafana/SageMaker Model Monitor

Bedrock Knowledge Bases

Job description

Robots & Pencils is seeking a Senior Data Engineer to design, build, and deliver the data and AI infrastructure behind an enterprise AI platform. You will work with AWS Services and cross-functional teams on a scaling observability data platform, from an initial pilot to full automation, focusing on data pipelines, instrumentations, and agent-enablement tooling.

The role emphasizes reliability, security, and scalability, with collaboration among senior engineers to shape architecture and