4 jobs in Integral Privacy Technologies

Work Arrangement: In office, five days per week

Integral is building the independent privacy layer for AI.

AI depends on real-world data, but the most valuable datasets are often proprietary, regulated, or sensitive. Integral enables organizations to transform these datasets into compliant, AI-ready data assets while preserving their analytical value.

Our platform brings together privacy assessment, data engineering, statistical methodology, expert review, continuous monitoring, and audit-ready documentation. We help AI builders access defensible, training-ready data and help data owners expand the value of their information without assuming unnecessary privacy risk.

Integral works across complex data environments, including healthcare and clinical records, behavioral and consumer information, and enterprise operational data.

We are an early-stage company working on difficult technical and product problems at the intersection of AI, data infrastructure, privacy, and compliance.

Integral is hiring its first dedicated Product Manager.

As our Founding Technical Product Manager, you will help define not only what we build, but how product development operates across the company.

You will work directly with company leadership, Engineering, Customer Solutions, Privacy Operations, and customers to translate complex data and privacy problems into scalable product capabilities. You will develop a deep understanding of Integral’s technical systems, customer workflows, statistical methodologies, and commercial strategy—and use that understanding to determine where the product should go next.

This is not primarily a project-management or backlog-administration role. You will be expected to form strong product opinions, investigate technical details, write clear requirements, make difficult prioritization decisions, and drive important initiatives from discovery through launch and adoption.

Because you will be our first Product Manager, you will also help establish the foundational processes, standards, and habits that allow Integral to build products effectively as the company grows.

Own Product Strategy and Prioritization

• Partner with company leadership to translate Integral’s vision into a clear and actionable product strategy.
• Develop and maintain a product roadmap grounded in customer needs, company priorities, market opportunities, and technical realities.
• Identify which customer problems should become scalable platform capabilities and which should remain services, configurations, or implementation‑specific solutions.
• Evaluate opportunities across privacy assessment, data sanitization, workflow automation, integrations, documentation, monitoring, and AI‑ready data delivery.
• Make thoughtful prioritization decisions across customer commitments, platform investments, technical debt, research initiatives, and emerging commercial opportunities.
• Clearly communicate the reasoning, evidence, assumptions, and tradeoffs behind product decisions.

Develop Deep Technical Product Understanding

• Build a working understanding of Integral’s system architecture, data models, APIs, processing pipelines, integrations, and technical constraints.
• Work closely with engineers to understand how data moves through the platform and where product decisions affect scalability, reliability, security, and maintainability.
• Participate meaningfully in technical design conversations without attempting to dictate engineering implementation.
• Translate between customer language, privacy and statistical methodology, business requirements, and technical system behavior.
• Help determine when the team should build a rapid customer solution, create a reusable product abstraction, invest in foundational infrastructure, or decline to build.
• Develop sufficient technical depth to independently investigate product behavior, identify gaps, and ask high‑quality questions.

Lead Product Discovery

• Work directly with customers and internal teams to understand complex data, privacy, compliance, and AI workflows.
• Conduct customer interviews, implementation reviews, workflow mapping, and product feedback sessions.
• Separate underlying customer problems from requested features or proposed solutions.
• Identify recurring patterns across customer engagements that can inform the broader product.
• Validate new concepts through prototypes, technical exploration, customer feedback, data analysis, and focused experimentation.
• Develop a clear understanding of how customers currently assess, sanitize, document, monitor, and deliver sensitive data.

Turn Ambiguity Into Clear Product Direction

• Convert complex and incomplete information into clear problem statements, product requirements, workflows, and success criteria.
• Write high‑quality product requirement documents that explain the customer problem, context, intended outcome, scope, constraints, risks, dependencies, and open questions.
• Break broad initiatives into focused phases that enable the team to deliver value and learn quickly.
• Define expected system behavior, edge cases, permissions, failure states, and operational requirements.
• Ensure that engineers understand both what is being built and why it matters.
• Make timely decisions when requirements change, technical constraints emerge, or new customer information becomes available.

Partner Closely With Engineering

• Work with engineers throughout discovery, technical design, implementation, testing, release, and iteration.
• Create strong feedback loops during development rather than treating requirements as a one‑time handoff.
• Balance speed, product quality, customer urgency, and long‑term platform durability.
• Help the team establish appropriate scope and avoid both unnecessary complexity and overly narrow one‑off solutions.
• Remove ambiguity, resolve product questions, and unblock execution.
• Build trusted relationships with engineers through clarity, sound judgment, responsiveness, and respect for technical expertise.

Productize Customer and Privacy Workflows

• Partner with Customer Solutions and Privacy Operations to identify manual or service‑heavy workflows that can be standardized or automated.
• Convert lessons from customer implementations into repeatable product functionality.
• Determine where expert review and human judgment should remain central and where technology can improve speed, consistency, and scale.
• Help design products that support both technical users and privacy, compliance, legal, and operational stakeholders.
• Ensure that customer‑facing outputs are clear, traceable, defensible, and useful in downstream review or procurement processes.
• Reduce the time and internal effort required to bring new customers and datasets onto the platform.

• 5+ years of product management experience, including ownership of technically complex B2B or enterprise software products.
• Experience working on data infrastructure, developer platforms, APIs, workflow systems, enterprise integrations, AI or machine learning products, security, privacy, governance, or similarly technical products.
• Demonstrated ability to develop product strategy and independently lead major initiatives from discovery through launch.
• Strong technical fluency and the ability to participate credibly in conversations about APIs, data models, processing pipelines, integrations, system architecture, and infrastructure tradeoffs.
• Experience translating complex customer or business requirements into clear technical product requirements.
• Strong product judgment and the ability to prioritize across customer value, company strategy, technical feasibility, implementation effort, and long‑term platform needs.
• Excellent written communication and the ability to produce clear, structured product requirements and decision documents.
• Strong customer discovery skills, including the ability to uncover the underlying need behind a requested feature.
• Experience working directly with enterprise customers and navigating technical, operational, legal, and executive stakeholders.
• Comfort operating with incomplete information, limited process, and changing priorities.
• A high level of ownership and a willingness to move between strategic thinking and detailed execution.
• A low‑ego, highly collaborative working style.
• Must be authorized to work in the United States without requiring sponsorship.

Expected Salary Range: $140k - $165k

Integral is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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 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

• 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 to reason about scalability, reliability, latency, security, and data integrity
• Interest in AI-enabled products, data infrastructure, or building backend systems that support AI/ML workflows
• Energized by fast-paced startup environments—you\'re excited to build, iterate, and wear multiple hats as the company scales
• Strong communication skills and ability to collaborate effectively with product, engineering, and customer-facing teams
• An ownership mentality—you proactively identify gaps, improve systems, and drive projects from idea through production

• Experience building data platforms, workflow engines, developer platforms, or infrastructure for data-heavy products
• Experience with AI/ML infrastructure, LLM applications, retrieval systems, model-serving workflows, evaluation pipelines, or data labeling systems
• Experience working with healthcare data, regulated data, privacy-preserving systems, or enterprise compliance requirements
• Experience with Postgres, Redis, Kafka, Airflow, Celery, Spark, or similar data/backend infrastructure tools
• Experience building systems that process large volumes of structured and unstructured data
• Experience with observability tools, distributed tracing, metrics, logging, and incident response
• Experience working in early-stage or high-growth startup environments
• Familiarity with security best practices for data-intensive systems, including access controls, auditability, encryption, and secure deployment patterns

• Competitive salary commensurate with experience
• Meaningful equity in a high-growth healthcare technology company
• Comprehensive health, dental, and vision insurance
• Daily company provided lunches
• Monthly wellness reimbursement
• Quarterly team offsites and semi-annual full company offsite
• Expected Salary Range / Equity: ($170k-200k) • 0.01%

Integral is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Integral Privacy Technologies is seeking a Senior Backend Software Engineer in San Francisco, California to build the core systems of their data operations platform. You'll design, develop, and scale backend services and APIs, ensuring sensitive data is usable and secure for healthcare.

This role requires strong backend engineering experience, proficiency in programming languages, and familiarity with cloud technologies. Integral offers competitive salary, equity, and comprehensive benefits.