Staff Software Engineer, Data

Gradial is building the AI-native system of work for enterprise marketing. Our agents turn ideas into live campaigns by executing across the tools, teams, and workflows enterprises already use—from content authoring and campaign assembly to quality assurance and brand compliance. We give marketers and creatives more time to shape brands, understand customers, and create work that moves people.

We’re tackling some of the hardest problems in applied AI: building agent harnesses, sandboxed execution environments, and orchestration that enable agents to plan, act, and verify their work reliably at enterprise scale. We’re growing rapidly, winning Fortune 500 and enterprise customers including AWS, T-Mobile, and Prudential. Our $65 million Series C led by Insight Partners is accelerating that momentum.

Join us to help define how people and AI agents work together. We move with urgency, reason from first principles, and take ownership from idea to customer impact. You’ll shape the product, own consequential problems, and build systems that some of the world’s leading brands depend on every day.

The Role

As a Staff Software Engineer, Data at Gradial, you will be our first dedicated data platform engineer, owning the platform end to end while staying deeply hands-on. You will shape the data layer behind our product, from Postgres data modeling and multimodal indexing and search to the pipelines that keep large, fast-changing enterprise content in sync across images, PDFs, text and other document types.

Your ownership will also extend to the company-wide data platform, including the warehouse and self-serve exploration tools that help teams across engineering and go-to-market make better decisions from reliable data. You will decide what to build first, build it and shape how Gradial uses data as we scale.

What You’ll Own

Define and execute the roadmap for Gradial’s data platform across product, engineering and company-wide data needs.

Own data modeling for our production databases, designing schemas and access patterns that scale with the product.

Lead the evolution of multimodal indexing and search across images, documents and text, with a focus on retrieval quality, performance and reliability.

Build and own reliable data pipelines across production databases, product events and third-party systems.

Build the warehouse, governed metrics and self-serve tooling that help teams answer their own questions with confidence.

Instrument the customer lifecycle from first lead through delivered value, giving teams a clear view into how customers move through the Gradial platform.

Set the standard for data quality, contracts and observability as our product and data surface area grow.

Make pragmatic architecture and build-vs-buy decisions that balance speed, scalability and cost.

What We’re Looking For

8+ years of experience in software engineering, data engineering or related roles with ownership of complex data systems. You've chosen the stack, not only operated one.

Proven success defining and building data architecture in fast-moving, high-growth environments.

Deep expertise in relational database design, including schemas, indexing, query patterns and consistency tradeoffs.

Strong experience building production data pipelines, warehouses and analytical data models.

Experience building production search systems, including embedding-based or hybrid retrieval and evaluating retrieval quality.

A track record of shipping reliable production code and making sound architecture decisions across complex systems.

Strong judgment in ambiguous environments, with the ability to prioritize, make pragmatic tradeoffs and build without an established playbook.

Ability to work effectively across engineering, leadership and non-technical teams to turn business needs into durable data systems.

Nice to Have

Experience as an early data hire at a high-growth B2B SaaS or AI-native company.

Experience with multimodal retrieval, LLM or agent data infrastructure.

Experience building data foundations for customer and revenue analytics in B2B SaaS.

The salary range for this position is $175,000 – $265,000 annually . Final compensation will be determined based on factors such as experience, skills, and qualifications.

What we offer

Performance-based annual bonus

Meaningful equity awards

Medical, dental & vision (fully covered for employees with 75% for dependents)

Fertility & family-planning support

401k plan

Unlimited PTO

A beautiful Seattle office with a gym, sauna, and bike parking

Free lunch three days a week in our HQ

A front-row seat to building category-defining AI infrastructure

You'll thrive here if you

Learn quickly, actively seek out new challenges, and regularly reconsider “how it’s always been done.”

Want to have real impact with zero bureaucracy.

Have an innate drive for being 1% better than the day before, building towards greatness.

Embrace AI as a core tool for problem-solving, innovation, and scale.

Show customer-obsession (internal or external), high ownership/accountability, and bias for action.

Communicate clearly, directly, with curiosity, and assuming good intentions.

Thrive in fast-paced, hyper-growth environments where building better > maintaining status quo.

AI Literacy & Interviewing Tools

As an AI-first company, we prioritize AI literacy as a core competency in our hiring decisions. We’re excited by candidates who thoughtfully apply AI tools in their work, but during interviews we’re focused on you. This is your opportunity to show how you think, communicate, and solve problems. Over-reliance on AI-generated responses during the interview process (especially when it obscures your own voice) will result in disqualification. We want to understand your unique perspective and how you approach challenges, both with and without AI.

Gradial is dedicated to creating an environment where diverse perspectives are valued and all team members can grow. We offer competitive compensation, equity, flexible work hours, comprehensive benefits, and a collaborative culture focused on learning and impact.