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Senior Backend Software Engineer

💼 Full-time🗓 2026-07-31

Core

Design, develop, and scale backend services, APIs, data pipelines, and infrastructure for a data operations platform handling sensitive, regulated healthcare data and AI workflows.

Role type

Senior Backend Software Engineer

Builds

Scalable backend services, data ingestion/transformation pipelines, and cloud-native infrastructure for AI-enabled data operations.

Domain

Healthcare data operations, AI/ML infrastructure, cloud-native systems

Deliverable

production ML models | product features | infrastructure

Required skills

Backend engineering, distributed systems, data pipeline design, database optimization, cloud platforms, containerization/orchestration, event-driven systems, system debugging, clean code practices

Preferred skills

Experience with Python/Go/Rust/TypeScript, working in ambiguous startup environments, rapid prototyping

Technologies

AWS, GCP, Azure, Docker, Kubernetes, Terraform, CI/CD systems

Responsibilities

Design and maintain backend services, prototype and productionize support for new data modalities, develop scalable APIs and microservices, optimize data ingestion and delivery pipelines, improve system performance and observability, debug complex production issues, contribute to technical architecture reviews

Seniority

Senior, hands-on IC

Rewrite
## About the Role De-identification is really hard. In the best case scenario it involves extracting text and visual elements, running probabilistic models to detect sensitive elements, and replacing them with high quality replacement values. New data types and modalities are being purchased and activated every day and Integral's platform has to incrementally handle the ever growing corpus of data and new sensitive entities in the AI ecosystem. We're looking for a Senior Backend Software Engineer to help build the core systems powering Integral's data operations platform. You'll design, develop, and scale the backend services, APIs, data pipelines, and infrastructure that make complex proprietary, regulated, and sensitive data usable, reliable, and secure for our customers. You'll be joining at a pivotal moment as we scale our engineering team and expand the backend foundation of our platform. This role sits at the center of Integral's product and engineering work. You'll partner with Product, Solutions Engineering, Customer Solutions, and other engineers to translate complex sensitive data workflows into scalable platform capabilities. This is a deeply technical backend role for someone who enjoys building high-performance systems, working close to the data layer, and solving hard infrastructure problems in ambiguous environments. You'll work across distributed systems, service architecture, data ingestion, workflow automation, database optimization, and cloud-native infrastructure. You'll also help build the backend foundation for AI-enabled data operations. That may include systems that support data processing, model workflows, automation, retrieval, evaluation, and secure delivery of regulated healthcare data. This is not an ML research role; it's a backend engineering role for someone excited to build the systems that make AI and data-intensive workflows production-ready. ## What You'll Do - Design, build, and maintain backend services that power Integral's data operations platform - Rapidly prototype and productionize support for new data modalities, moving from ambiguous customer requirements or emerging research to pragmatic backend solutions in tight timelines - Support deadline-driven customer work from time to time, balancing speed, quality, and long-term platform durability - Develop systems that can adapt to evolving AI/ML use cases across healthcare, enterprise, and other regulated or sensitive data environments - Develop scalable APIs, microservices, and internal tools that support core product workflows - Build and optimize data ingestion, transformation, validation, and delivery pipelines for high-volume healthcare data - Work across databases, queues, object storage, and distributed processing systems to support reliable data movement at scale - Improve system performance, reliability, observability, and fault tolerance across backend services - Design backend architecture that is secure, maintainable, and able to scale with customer and product growth - Partner with Product and Solutions Engineering to translate complex customer and data infrastructure needs into durable platform capabilities - Build backend systems that support AI-enabled workflows, including data preparation, automation, retrieval, evaluation, and model-adjacent infrastructure - Optimize database schemas, queries, indexing strategies, and storage patterns for performance and maintainability - Develop cloud-native infrastructure using tools and platforms such as AWS, Docker, Kubernetes, Terraform, and CI/CD systems - Create clean abstractions, reusable services, and internal frameworks that help the engineering team move faster - Debug complex production issues across services, infrastructure, data pipelines, and customer environments - Contribute to technical design discussions, architecture reviews, and engineering best practices - Operate with high ownership in a fast-moving startup environment where priorities evolve quickly and ambiguity is the norm ## What We're Looking For - 3-6+ years of experience as a backend software engineer, infrastructure engineer, data platform engineer, or similar technical role - Strong backend engineering experience building production-grade services, APIs, and distributed systems - Experience designing and operating scalable data pipelines, ETL/ELT workflows, or data-intensive backend systems - Proficiency in one or more backend programming languages such as Python, Go, Rust, TypeScript, or similar - Strong understanding of databases, data modeling, query optimization, indexing, and transactional systems - Experience with cloud platforms such as AWS, GCP, or Azure - Experience with containerization, orchestration, and infrastructure tooling such as Docker, Kubernetes, Terraform, or similar - Familiarity with event-driven systems, queues, background jobs, workflow orchestration, or distributed processing patterns - Ability to write clean, maintainable, well-tested code and make thoughtful engineering tradeoffs - Comfort working across the full backend stack, from API design and business logic to infrastructure, observability, and production debugging - Strong systems thinking and an ability
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