Forward Deployed Engineer, Unstructured AI

Details

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. 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 New York office. Our hybrid model means you’ll work from the office at least two days each week.

Responsibilities

• 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 and guide 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 — make 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 to identify opportunities to improve product experience.
• Keep cross-functional teams aligned through clear communication, prioritization, and follow-through.

Requirements

• 2+ years of software engineering or technical deployment experience, ideally involving enterprise integrations, AI data processing, or customer-facing delivery.
• Strong proficiency in Python for data processing, API development, and integrations.
• Experience writing and reviewing production-grade backend code (explicit mention of FastAPI).
• 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).
• Familiarity with CI/CD, monitoring, and debugging tools.
• Experience with LLM-based or AI-driven enrichment models (classification, extraction, deduplication, PII detection).
• Familiarity with metadata systems, data cataloging, or document AI workflows.
• Background in data governance, sensitive data detection, or enterprise integrations (examples: Collibra, Databricks, Snowflake).
• 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 modeling 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 in communication and stakeholder-management across technical and business teams.
• Calm and structured in decision-making under tight timelines or ambiguity.

Measures of Success

Within your first month:

• Develop a deep understanding of enterprise unstructured data management, including document pipelines, metadata systems, and retrieval architectures.
• Partner with senior product leadership and ship your first end-to-end feature across the stack (backend, infrastructure, and UI).

Within your third month:

• Deploy the product and your features in multiple Fortune 500 customer environments, often working inside the customer’s cloud and data perimeter.
• 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:

• 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.

Compensation

• Base salary range: $140,000 - $175,000 per year. This position is not eligible for additional commission-based compensation. Salary offers are based on experience, skills, and location.
• In addition to base salary: equity ownership opportunities, bonus potential, a Flex Fund monthly stipend, pension/401(k) plans, and more.

Benefits

Collibra offers flexible benefits designed to support a diverse range of needs, including competitive compensation, health coverage, time off, and inclusion initiatives. Learn more via Collibra’s careers pages linked in the original posting.