Lead SageMaker Platform Engineer

Our team is undergoing a large data + ML migration onto AWS SageMaker Pipelines. We deploy via Terraform and GitHub Actions across multiple AWS accounts aligned to our SDLC, sync model artifacts to a shared-services account, and validate models in dedicated testing accounts. Data is sourced primarily from Redshift, including trusted identity propagation., * Pair with our data scientists in live debugging sessions to diagnose and fix broken SageMaker pipelines and get them through the SDLC to prod.

• Rapidly triage failures using AWS logs and telemetry (CloudWatch, CloudTrail, SageMaker pipeline/execution logs, etc.) and pinpoint root causes.
• Untangle permissions issues across pipeline execution roles, cross-account access, and CI/CD identity (GitHub Actions OIDC, Terraform-managed IAM).
• Help debug cross-account model artifact syncing (shared services) and the testing-account validation flow.
• Level up the team’s mental model for how the platform works and where to look when things break., At Perficient, we promise to challenge, champion, and celebrate our people. You will experience a unique and collaborative culture that values every voice. Join our team, and you’ll become part of something truly special. We believe in developing a workforce that is as diverse and inclusive as the clients we work with. We’re committed to actively listening, learning, and acting to further advance our organization, our communities, and our future leaders… and we’re not done yet. Perficient, Inc. proudly provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, genetic information, marital status, amnesty, or status as a protected veteran in accordance with applicable federal, state and local laws. Perficient, Inc. complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Perficient, Inc. expressly prohibits any form of unlawful employee harassment based on race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or covered veterans. Improper interference with the ability of Perficient, Inc. employees to perform their expected job duties is absolutely not tolerated. Disability Accommodations: Perficient is committed to providing a barrier-free employment process with reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or accommodation due to a disability, please contact us.

• Expert-level AWS operational experience, especially debugging via logs and telemetry (CloudWatch Logs/Metrics, CloudTrail, X-Ray or equivalent) - can move from a vague failure to a root cause fast.
• Deep IAM / permissions expertise in a multi-account setup: execution roles, assume-role/cross-account access, resource policies, KMS/encryption permissions, and reasoning about “who is allowed to do what, as which principal.”
• Hands-on SageMaker experience, including SageMaker Studio and SageMaker Pipelines - knows how pipelines are defined, deployed, and executed, and where to look when a step fails. (Operating/debugging, not modeling.)
• Multi-account AWS experience aligned to an SDLC (dev/test/prod), including cross-account resource sharing and promotion patterns.
• Comfortable working embedded and hands-on: live pairing, screen-sharing, and debugging under time pressure.
• Strong communicator who can explain why something broke and how to avoid it next time.

Nice to Haves:

• Terraform experience, especially managing IAM and SageMaker/data infrastructure as code.
• GitHub Actions CI/CD experience, particularly OIDC-based authentication to AWS (no long-lived keys) and the IAM trust policies behind it.
• Experience with Amazon Redshift, and ideally trusted identity propagation / IAM Identity Center integration.
• Some ML/MLOps background - enough to speak the language of model training, artifacts, and deployment (helpful, not required).
• AWS certifications (e.g., Solutions Architect Pro, DevOps Engineer Pro, ML Specialty) as a signal, though hands-on evidence matters more.

Lead the build and production rollout of SageMaker Pipelines: pair with data scientists to debug pipelines, triage failures via AWS logs/telemetry, resolve multi-account IAM and cross-account artifact sync issues, improve CI/CD (Terraform, GitHub Actions), and raise the team’s operational knowledge of the platform. The summary above was generated by AI

About UsPerficient is the global AI and technology consulting firm disrupting the traditional consulting model. Powered by our 7,000+ advisors, engineers, and designers, Perficient implements AI-first solutions that break conventions and deliver outcomes that matter. Proudly serving clients that represent the world’s most innovative brands, and in collaboration with our powerful technology partner ecosystem, we bring deep industry expertise and data-driven design to redefine how businesses run and succeed. Perficient is different. For real. Learn more at perficient.com.