Software Engineer

Joining Collibra’s Unstructured AI Team

We’re shaping the way some of the largest organizations in the world manage data by helping customers connect the right data and insights for all Data Citizens. We are building a team of exceptional people to help us deliver on that promise. As a Deployed Engineer, you are the guiding force behind bringing Collibra's product and vision to customers and prospects. Engineers establish knowledgeable and trusted relationships from day one and serve as thoughtful technical advisors.

This is a hybrid role based in our Raleigh office. Our hybrid model means you’ll work from the office at least two days each week. This setup helps us stay connected, work more closely together, and keep making progress as a team.

Forward Deployed Engineer at Collibra are responsible for

• Own end-to-end technical delivery of Unstructured AI deployments — from first prototype to stable production across enterprise environments.
• Build and scale full-stack systems that process and enrich large volumes of unstructured content (PDFs, contracts, reports, and other document types).
• Embed closely with customer and field teams to understand their metadata, governance, and security needs - guiding how Unstructured AI integrates into their broader Collibra stack.
• Scope work, sequence delivery, and remove blockers early to ensure fast iteration cycles between product, research, and deployment teams.
• Balance scope, speed, and quality - making clear trade-offs to keep pilots moving and convert them into production rollouts.
• Codify repeatable patterns from customer projects into reusable connectors, enrichment modules, or playbooks that accelerate future deployments.
• Feed field insights back to Product and Research, identifying opportunities to improve product experience.
• Keep cross-functional teams aligned through clear communication, prioritization, and follow-through.

You have

• Shipped complex systems under ambiguity - balancing speed and precision in real customer environments.
• Written and reviewed production-grade code across backend (Python, FastAPI).
• Built or deployed document-processing systems and are comfortable with CI/CD, monitoring, and debugging tools.

• 2+ years of software engineering or technical deployment experience,  ideally involving enterprise integrations, AI data processing, or customer-facing delivery.
• Strong proficiency in Python (data processing, API development, and integrations).
• Proven ability to deliver production-grade systems that process large-scale unstructured data (PDFs, text, documents).
• Solid understanding of data pipelines, microservice architecture, and API design.
• Experience with cloud infrastructure (AWS, GCP, or Azure), Infrastructure as Code (Terraform) and containerization (Docker / Kubernetes).
• Experience with LLM-based or AI-driven enrichment models (classification, extraction, deduplication, PII detection).
• Familiar with metadata systems, data cataloging, or document AI workflows.
• Background in data governance, sensitive data detection, or enterprise integrations (Collibra, Databricks, Snowflake, etc.).
• A track record of codifying repeatable deployment patterns into tools, SDKs, or frameworks.
• Knowledge of security, compliance, and model evaluation best practices.

You are

• Capable of communicating clearly across engineering, product, and field teams, ensuring alignment from prototype to rollout.
• Experienced in spotting risks early, course-correcting without friction, and model composure when delivery timelines are tight.
• Someone who cares deeply about data quality, precision, and governance.
• Willing to gain hands-on experience with modern frontend development.
• Able to translate customer requirements into technical plans and deliver end-to-end.
• Strong communication and stakeholder-management skills across technical and business teams.
• Calm, structured decision-making under tight timelines or ambiguity.

Measures of Success

Within your first month, you will…

• Develop a deep understanding of how enterprises manage and transform unstructured data, including document pipelines, metadata systems, and retrieval architectures.
• Partner closely with former YC founders and senior product leadership to see how we run a fast, startup-style execution motion inside a scaled organization. You will then ship your first end-to-end feature across the stack (backend, infrastructure, and UI), directly improving the product used by real customers.

Within your third month, you will…

• Deploy the product and your features in multiple Fortune 500 customer environments, often working inside the customer’s cloud and data perimeter. You will serve as the connective tissue between GTM, Product, Engineering, and Customer teams, translating customer feedback into product direction and execution plans.

Within your sixth month, you will…

• Become an expert in context engineering, designing how data, metadata, and domain knowledge flow into AI systems to maximize reliability, relevance, and decision quality.
• Independently lead complex deployments, transforming unstructured and structured data to support AI-driven decision making at enterprise scale. You will use the Unstructured AI platform to build enterprise-grade AI products within customer environments, shaping how AI agents reason over real-world data.

Compensation for this role

The standard base salary range for this position is $140,000.00 - $175,000.00 per year. This position is not eligible for additional commission-based compensation. Salary offers are based on a combination of factors, including, but not limited to, experience, skills, and location.

In addition to base salary, we offer equity ownership at every level, bonus potential, a Flex Fund monthly stipend, pension/401k plans, and more.