Senior Platform Engineer, Data & AI

National Debt Relief, LLC.•,

1d•$140,000 - $160,000•Remote

About The Position

National Debt Relief (NDR) is seeking a Senior Platform Engineer, Data & AI to help build and scale the next generation of our enterprise data and AI platform. This role sits within the Data Engineering organization and will focus on building the application and service layer that powers our Customer Data Platform (CDP), AI products, and operational data systems. A primary focus of this role will be designing and implementing cloud-native services in AWS that sit in front of core data platforms including PostgreSQL, Snowflake, and other enterprise data systems. These services will support internal applications, customer intelligence initiatives, marketing activation, analytics, and AI-driven products. While this role will collaborate closely with our ML Ops team and contribute to shared platform initiatives, the primary emphasis is backend platform engineering, API development, and operational data services. The ideal candidate combines strong software engineering fundamentals with experience building production-grade backend systems, cloud-native services, APIs, and data platforms.

Requirements

Bachelor’s degree in related field preferred.
5 years of experience building production backend systems, platform services, cloud-native applications, or data platforms.
Strong experience building and operating APIs using FastAPI, Flask, Django, or similar frameworks.
Strong PostgreSQL experience including schema design, query optimization, indexing, and performance tuning.
Hands-on experience with AWS cloud services and modern cloud architecture patterns.
Strong experience with Docker and containerized application deployment.
Experience designing distributed systems and service-oriented architectures.
Experience implementing CI/CD workflows and modern software engineering best practices.
Experience with observability, monitoring, logging, and alerting frameworks.
Experience with pytest testing frameworks and patterns, including unit, integration, and end-to-end testing.
Experience with Bash and Unix-based environments.
Expert-level Python development experience.
Strong SQL expertise and experience working with enterprise data platforms such as Snowflake.
Familiarity with Infrastructure-as-Code tooling such as Terraform.
Strong communication and collaboration skills across Data Engineering, ML Ops, Product, and Analytics teams.
Ability to operate independently and help define platform standards and architecture direction.
Computer competency and ability to work with a computer.
Prioritize multiple tasks and projects simultaneously.
Exceptional written and verbal communication skills.
Punctuality expected, ready to report to work on a consistent basis.
Attain and maintain high performance expectations on a monthly basis.
Work in a fast-paced, high-volume setting.
Use and navigate multiple computer systems with exceptional multi-tasking skills.
Remain calm and professional during difficult discussions.
Take constructive feedback.
Available for full-time position.

Nice To Haves

Experience deploying model-serving or inference APIs.
Experience with ECS, EKS, Kubernetes, or serverless AWS architectures.
Experience supporting Customer Data Platforms (CDPs), customer 360 initiatives, or marketing technology ecosystems.
Experience with event-driven architectures, CDC pipelines, or streaming platforms.
Experience in financial services, fintech, or other regulated industries.
Strong software engineering fundamentals, including design patterns and maintainable architecture practices.

Responsibilities

Design, develop, and maintain scalable backend services and APIs that power NDR’s Customer Data Platform and AI ecosystem.
Build secure, high-performance service layers on top of PostgreSQL, Snowflake, and other enterprise data platforms.
Design and implement RESTful APIs and service-oriented architectures using Python, FastAPI, and modern backend engineering practices.
Develop cloud-native applications and platform services within AWS using scalable, resilient architectural patterns.
Partner with Data Engineering teams to expose governed data products and operational datasets through reusable platform services.
Collaborate with ML Ops and Data Science teams to support model serving, feature delivery, inference workflows, and AI-powered applications.
Design and implement authentication, authorization, auditing, and governance controls for data and platform services.
Build and maintain CI/CD pipelines, Infrastructure-as-Code, testing frameworks, and deployment automation.
Establish observability, monitoring, logging, and alerting standards across platform services and APIs.
Optimize platform reliability, scalability, performance, and operational efficiency.
Contribute to platform architecture decisions and help define engineering standards across Data Engineering and AI initiatives.
Document system architecture, API contracts, operational processes, and engineering best practices.