Privacy Program Engineer

Fireworks

1d • $166,000 - $175,000

About The Position

Fireworks is seeking a Privacy Program Engineer to lead the technical aspects of its privacy program. The company has achieved ISO 27001, ISO 27701, ISO 42001, and SOC 2 Type II certifications and actively manages GDPR and CCPA/CPRA programs. This role requires a technical individual who will write scripts, queries, and automation to maintain and enhance the privacy program. The engineer will own workstreams such as data subject requests, data inventory and ROPA, and privacy reviews for new vendors and features. Reporting to the Privacy Lead, this position is crucial for the technical expertise within the privacy team and will involve owning the design and direction of technical systems, automations, and tools to ensure compliance with privacy obligations. The role is for someone who builds systems and leverages AI tooling, automation, and scripting to minimize manual privacy work, possesses strong technical skills including database querying and automation with code or workflow engines, takes initiative on projects, and demonstrates extreme ownership.

Requirements

• 4–7 years of experience in privacy, GRC, IT audit, information security, or a closely related field, with meaningful hands-on privacy work.
• Working knowledge of GDPR and CCPA/CPRA, and familiarity with ISO 27701, ISO 27001, ISO 42001, SOC 2, and NIST.
• Hands-on experience with technical privacy operations: data subject requests, ROPA or data inventory maintenance, privacy impact assessments, or retention enforcement.
• Evidence that you automate your own work - AI tooling, scripts, workflow builders, or aggressive use of a privacy/GRC platform's automation features. Tell us what you built and what it replaced.
• Working proficiency in SQL and at least one scripting language - enough to query a warehouse, call an API, parse a schema, and automate a recurring task without help.
• Hands-on familiarity with cloud environments (AWS, GCP, or Azure): IAM and access scoping, logging, data stores and their retention behavior, and how to find where data actually lives and how it’s used.
• Strong written communication; you can translate privacy requirements into language engineers, customers, and non-technical employees understand.

Nice To Haves

• Built something with an LLM API or agent framework that other people relied on.
• Experience with de-identification or synthetic data techniques.
• Exposure to data lineage or catalog tooling (dbt, DataHub, Atlan, Monte Carlo, OpenMetadata).
• Worked on a privacy or security problem at an AI/ML company specifically - model data flows, inference logging, training data provenance.
• Startup or fast-growing SaaS background.

Responsibilities

• Build the privacy automation layer: scripts, scheduled jobs, API integrations, and LLM-based agents that handle request routing, evidence collection, assessment intake, and control monitoring.
• Own the data subject rights (DSR) program and the system behind it: build the intake, identity verification, fan-out across data stores, and fulfillment tracking as an automated pipeline rather than a checklist, with the audit trail generated as a byproduct.
• Build and maintain a data inventory and ROPA that derives from the environment rather than from interviews: pull from cloud APIs, warehouse metadata, IaC, and service catalogs so the map updates when the systems do, and reconcile drift.
• Embed privacy into how we build: review designs and PRs for data handling, advise on de-identification, pseudonymization, tokenization, field-level encryption, and access scoping, and give engineers a concrete pattern to use rather than a policy to read.
• Own retention and deletion as an engineering problem: translate retention requirements into concrete rules per data store, work with engineering on enforcement in pipelines and backups, and build the verification that proves deletion actually happened.
• Support consent management and preference handling across our web properties and product surfaces.
• Solve AI data problems directly: trace how customer data moves through training, fine-tuning, inference, and logging; validate zero-retention and isolation claims against what the platform actually does; and build the checks that keep those claims true as the platform changes.
• Take on additional privacy projects as the program evolves; we're a growing team with dynamic priorities.

Benefits

• Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
• Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
• Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
• Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed