Senior Backend Software Engineer

Healthcare data is among the most valuable, expansive, and regulated data in the world—spanning voice interactions, raw images, clinical notes, financial profiles, and more. This data underpins population health outcomes, research, reimbursement, and increasingly AI. But today's manual systems to process, optimize, and deploy this data are broken.

Our Agentic Data Operations Platform streamlines the full set of operations required to make sensitive data usable—from sourcing and compliance to governance and continuous delivery. Instead of relying on fragmented services and bespoke pipelines, enterprises use Integral to manage healthcare data end-to-end through a single, persistent platform.

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.

• Design, build, and maintain backend services that power Integral s data operations platform
• Rapidly prototype and product ionize 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

• 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…