Sr. AI Data Engineer

Description

The company is an applied AI engineering firm that designs and ships AI co-workers for enterprise operations, working with clients across consumer products, retail, education, energy, financial services, healthcare, and manufacturing. It is built on AWS, was founded in 2009, and has delivery centers in Canada, the United States, Eastern Europe, and Latin America. Teams average 15+ years of experience and the company commits to shipping production AI in 30 to 45 days.

The role is a senior data engineering position for a remote candidate in the United States. You will help build the data and AI infrastructure for an enterprise agentic AI platform, working as a key contributor on a cross-functional team with AWS Professional Services and embedded with a large enterprise client. The work moves an observability data platform from a single-agent pilot to a fully automated, end-to-end operations model, covering the agentic AI framework, data pipelines, observability, and service enablement. The system is already live and in flight, where reliability, security, and scalability matter.

The company builds AI systems for people working in real workflows, pairing engineering with creativity. The team values ownership, craft, and accountability for the work each person ships.

Responsibilities

• Design, build, and deploy data and AI/ML systems on AWS from concept to production, including data lake pipelines, observability instrumentation, and tuning for performance, reliability, and cost.
• Build the agentic AI framework, its tooling, and the service enablement around it, moving agent workloads from a single-agent pilot to a fleet-scale operating model.
• Maintain production platforms by monitoring for drift, debugging issues, and improving reliability and scalability over time.
• Use AI-forward coding tools such as Claude and Cursor in your daily work to deliver higher-quality output faster.
• Work closely with AWS Professional Services, client engineering, and data teams to keep the work aligned with platform and business goals.
• Explain technical tradeoffs, system behavior, and constraints in terms non-specialists can act on.
• Take part in code reviews and design discussions, raising concerns and giving useful feedback.
• Shape data and AI architecture decisions by weighing tradeoffs and long-term effects.
• Own meaningful work from start to finish, including the less visible tasks needed to get AI into production.
• Raise engineering standards through your own work and by mentoring more junior engineers when the chance arises.

Requirements

• 5+ years of professional software or data engineering experience, including 2+ years building data platforms and shipping AI/ML or agentic systems in production on AWS.
• Strong software engineering skills in Python and SQL, or similar languages.
• AWS Certified Data Engineer, Associate. Candidates without it will be considered if they have a clear, near-term path to earning it.
• Hands-on experience building data lakes on AWS with S3, Lake Formation, Glue, Athena, and Iceberg or Parquet. Exposure to streaming on Kinesis or MSK is a plus.
• 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 work enabling agents on AWS, including Amazon Bedrock Knowledge Bases, Guardrails, RAG, Bedrock Agents, and agent frameworks such as Strands Agents or LangGraph.
• Experience designing and shipping agentic AI systems in production.
• Experience with MLOps and LLMOps, including evaluating, deploying, and monitoring 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.
• Experience optimizing costs across storage, queries, compute, and model usage.
• Experience delivering solutions in a consulting or professional services setting alongside client and partner teams.
• Day-to-day, demonstrable use and knowledge of AI-forward coding tools such as Claude Code and Cursor.
• Strong problem-solving skills and sound judgment when working through ambiguous technical challenges.
• Nice to have: experience in regulated enterprise environments such as financial services.
• Nice to have: additional AWS certifications such as Machine Learning Engineer, Associate, Security, Specialty, or Solutions Architect, Professional.
• Nice to have: prior work with AWS Professional Services or other AWS partner delivery teams.
• Nice to have: open-source contributions or deep familiarity with the OpenTelemetry ecosystem.

Conditions

Remote position, located in the United States.

The salary range for this role is $119,514 USD to $164,899 USD. Final pay may fall above or below this range and the range may change. Placement within the range depends on factors such as education, certifications, experience, skills, seniority, geographic location, performance, shift, travel requirements, revenue-based metrics, collective bargaining agreements, and business needs.

Equal-opportunity statement is not included in the original.

Benefits

• Comprehensive benefits for eligible employees, including paid time off, medical, dental, and vision insurance, and a 401(k).