Senior AI Platform Engineer

Location: Charlestown, MA

Onsite Flexibility: Remote

• Position Type: Right to Hire
• Pay Rate: $70.00 / Hour (USD)
• Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

The AI Platform team is scaling rapidly, driven by the rollout of the AI Platform Developer Kit (AIP Kit) and a growing cloud footprint on AWS. We are hiring a US-based Senior Platform Engineer to serve as a technical anchor for the platform. This is first and foremost a cloud platform engineering role — Python, AWS, infrastructure-as-code, CI/CD, and developer tooling. The platform serves AI workloads, so you should be conversant with AI services and comfortable using AI tools in your work, but deep machine-learning expertise is not required. You will shape architecture, harden the platform's security posture in partnership with the security organization, lead the AIP Kit rollout as the DevOps standard, and provide technical leadership and code review for a blended onshore/offshore delivery team. The role supports major FY26 initiatives including the Call Center AI pipeline, Intelligent Document Processing, self-service batch pipeline creation, automated IAM generation and validation, and platform cost management. You will work directly with cloud owners, data platform leadership, and business partners, so clear communication and visible ownership matter as much as engineering depth.

• Own architecture and design decisions for AI Platform services and pipelines, and represent the platform in architecture governance forums.
• Lead the rollout and adoption of the AIP Kit across the AI infrastructure portfolio: templates, standards, documentation, and developer onboarding.
• Design, build, and operate cloud services and pipelines on AWS — including pipelines that integrate AI/LLM capabilities through platform-provided interfaces such as Amazon Bedrock.
• Define and enforce the platform's security model in partnership with the security team: least-privilege IAM design, KMS encryption, secrets handling, and artifact integrity in the release pipeline.
• Apply sound testing discipline across the platform, including sensible quality gates for pipelines whose AI-driven outputs are non-deterministic.
• Set and uphold CI/CD and release standards (branching strategy, PR review, automated testing, environment promotion) across the team.
• Review code and mentor onshore and offshore engineers; unblock the delivery team and raise the overall engineering bar.
• Drive operational clarity: monitoring, alerting, structured logging, incident response, and cloud cost reporting/value justification for platform workloads.
• Partner with data platform, security, and business stakeholders on the joint AI/Data roadmap and cross-functional integrations (document processing, call recordings, data warehouse pipelines).

• 5 years of professional Python development, building, owning, and maintaining production applications (object-oriented design, testing, packaging).
• 3 years of hands-on AWS experience designing, building, and operating production workloads.
• 3 years of infrastructure-as-code experience with Terraform or CloudFormation (AWS CDK a plus).
• Working familiarity with AI: comfortable using AI coding assistants and LLM APIs, and able to learn AI services as the platform requires — deep ML or data-science expertise is not required.
• Working knowledge of AWS security fundamentals: IAM policy design and least privilege, KMS, and secrets management — with the ability to collaborate with a central security team on org-level controls.
• Strong CI/CD and release discipline: pipeline design, automated testing, and enterprise Git workflows with a clear point of view on branching strategies.
• Demonstrated technical leadership: code review, mentoring, and communicating design decisions to non-engineering stakeholders.

• Experience building LLM-powered applications with Amazon Bedrock or comparable model APIs (Anthropic, OpenAI, or self-hosted), including prompt design and evaluation of non-deterministic outputs.
• Experience with a workflow orchestration framework (Metaflow strongly preferred; Airflow, Step Functions, or similar), and willingness to go deep on Metaflow, which underpins the AI Platform.
• AWS-native observability experience: CloudWatch metrics/logs/alarms and CloudTrail for audit and troubleshooting.
• Amazon SageMaker experience (training, pipelines, or endpoints).
• TypeScript/JavaScript experience, particularly CDK constructs or internal tooling.
• Spark on EMR or other large-scale batch processing experience.
• Cloud cost management / FinOps exposure (cost allocation, estimation, reporting).
• Experience in healthcare, health plans, or other regulated environments (HIPAA/PHI data handling).
• Experience standardizing developer tooling or running an internal platform/developer-experience function ("platform as a product" mindset).

• Bachelor's degree in Computer Science or a related field, or equivalent practical experience.

• 5 years of professional Python development, building, owning, and maintaining production applications.
• 3 years of hands-on AWS experience designing, building, and operating production workloads.
• 3 years of infrastructure-as-code experience with Terraform or CloudFormation.

• This role is 100% remote; East Coast hours are expected.
• Regular collaboration with an offshore delivery team requires structured hand-offs, clear written communication, and strong documentation habits.

• Medical, Vision, and Dental Insurance Plans
• 401k Retirement Fund

GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada.

Job Number: 26-09719 Industry: Engineering