Senior AWS DevOps Engineer, Data and AI Platforms

Location: Houston, TX (Downtown), fully onsite 5 days per week, local candidates only

Duration: 6-Month Contract (W2)

Schedule: Standard Business Hours, 40 hours per week

Pay Rate: $99.00 - $103.00/hr

Our client, a leading midstream energy company headquartered in Houston, TX, seeks a Senior (Level III) Dev Ops Engineer to design, build, and run the Dev Ops capability for its AI and Data Engineering teams on AWS. Working directly with internal customers, this individual will design and document the overall Dev Ops solution architecture, then build the CI/CD pipelines, automation, and deployment paths that Data, ML, and AI Engineers use to ship data products, ML models, and GenAI applications.

The ideal candidate knows the data engineering space well (how Snowflake, dbt, and Airflow workloads are built, tested, promoted, and operated) and understands what it takes to take an ML or GenAI service to production.

Working with minimal supervision alongside Security, Compliance, Data Engineering, AI Engineering, and the wider Dev Ops team, the engineer will establish reusable, templated practices with required gates and governance built in, making the compliant path the easiest path for developers. This role suits a daily, proficient user of AI-assisted engineering tools who will help shape how the team uses AI. All work is documented and handed over so the client's Dev Ops staff can operate and extend it.

• Initially, help automate Security and Compliance processes into the CI/CD pipelines and the client's compliance tool using Terraform, Python, and Shell
• Build the first reusable, templated CI/CD paths for data and AI workloads, with the required gates and evidence included
• Take over Dev Ops work currently handled within the Data Engineering team
• Establish baseline observability and the first runbooks for the data and AI platform, and identify the highest-toil processes to automate first
• Collaborate with internal customers (Data, ML and AI Engineering teams and their stakeholders) to understand their needs, then design and document the overall Dev Ops solution architecture: delivery paths, environments, gates, tooling and operating model; record design decisions and their rationale so others can extend the design
• Own CI/CD and deployment automation for data and AI workloads:
  Snowflake and dbt change promotion, Airflow/Astronomer DAG deployment, and ML model and GenAI service release, across AWS, containerized clusters and on-premises environments
• Partner with the Infrastructure Platform Engineering team on Infrastructure as Code (AWS Cloud Formation, Terraform/Open Tofu, CDK) for multi-account AWS environments, and incorporate it into pipelines for data and AI platform services (S3, Glue, Athena, Lake Formation, Sage Maker, Bedrock, Lambda, ECS, RDS, IAM, VPC)
• Automate Cloud Formation stack/change set and Terraform plan/apply deployments, testing, and evidence
• Support MLOps practices, including model registries, pipeline automation, promotion across environments, and cost and guardrail controls for LLM-based systems
• Build reusable, versioned, templated pipelines and workflows that teams adopt rather than copy, with security and compliance controls built in by default
• Implement and automate required gates (approvals, segregation of duties, policy-as-code, scanning, change-ticket linkage) and produce auditable deployment evidence, working directly with Security and Compliance
• Make developer experience a first-class goal through self-service tooling, fast feedback, clear errors and good documentation, so the governed route is also the easiest; measure and improve it
• Build observability (metrics, logs, traces, dashboards, actionable alerting) and apply…