Sr. AI Data Engineer

Robots & Pencils is hiring a Senior Data Engineer to build and deliver data and AI infrastructure for an enterprise agentic AI platform. The role focuses on developing AWS data pipelines, observability, and agent enablement while helping scale a single-agent pilot into an automated operating model.

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
• Establish an agentic AI framework and the tooling and service enablement around it, taking agent workloads from a single-agent pilot toward a fully automated, fleet-scale operating model
• 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

Requirements:

• 5+ years professional software or data engineering experience, with 2+ years building data platforms and shipping AI/ML or agentic 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
• Hands-on experience with agent enablement on AWS, including Amazon Bedrock Knowledge Bases, Guardrails, RAG, and Bedrock Agents, and agent frameworks such as Strands Agents or LangGraph
• Experience designing and shipping agentic AI 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
• Experience in regulated enterprise environments such as financial services
• Additional AWS certifications such as Machine Learning Engineer – Associate, Security – Specialty, or Solutions Architect – Professional
• Prior work with AWS Professional Services or other AWS partner delivery teams
• Open-source contributions or deep familiarity with the OpenTelemetry ecosystem