Human Data Solutions Engineer

Encord • San Francisco, CA

33d • Onsite

About The Position

As a Human Data Operations & Solutions Engineer at Encord, you will sit at the intersection of technical sales and hands-on data operations. You are the expert who takes a prospect from first demo to a working proof of concept — not just by showing the platform, but by actually delivering a small-scale, high-quality annotation sample that demonstrates what best-in-class data operations looks like in practice. You'll own the full arc: leading technical discovery on demo calls, designing the annotation workflow, managing the delivery of sample datasets, and translating the results into a compelling case for the client. With a strong focus on robotics and autonomous driving, you'll be working with some of the most technically complex and data-intensive AI use cases in the industry.

Requirements

• 1-3 years of professional experience, ideally spanning strategy consulting, AI/technology operations, or customer-facing technical roles (Solutions Engineering, Technical Account Management, or similar)
• Proven ability to own complex, multi-stakeholder workflows end-to-end — from scoping and planning through execution, quality assurance, and client communication
• Working proficiency in Python or SQL, with the ability to query data, automate workflows, or audit annotation outputs
• Experience designing or optimising data operations processes with a strong eye for quality, consistency, and scalability — ideally involving human-in-the-loop or structured labelling workflows
• Demonstrated ability to engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients
• Hands-on experience with at least one major cloud platform (GCP, AWS, or Azure), including data storage and ML workflow patterns

Nice To Haves

• hands-on experience with computer vision, LiDAR, robotics sensor data, or autonomous driving datasets
• prior exposure to data annotation platforms or quality management frameworks
• experience in a customer-facing technical role at an AI company

Responsibilities

• Partner with Account Executives to lead the technical and operational strategy for complex enterprise sales cycles, co-owning the path to a successful proof of concept
• Lead deep technical discovery sessions with ML Engineers, MLOps leaders, and non-technical stakeholders to understand data requirements and design the right annotation workflow
• Manage end-to-end delivery of small-scale annotation POCs — translating complex AI requirements into clear instructions for annotation specialists, auditing outputs, and iterating on quality until the sample is client-ready
• Build and deliver tailored demonstrations that combine platform capability with live, real-world annotation results — particularly for robotics, autonomous driving, and multimodal sensor data (LiDAR, camera fusion, etc.)
• Act as a trusted advisor to clients on annotation workflow design, data quality, and the operational processes that underpin model performance
• Provide structured feedback and guidance to annotation teams during POC delivery, ensuring outputs meet the quality bar required to win client confidence
• Translate findings and operational results into clear value propositions for senior, non-technical stakeholders
• Serve as the voice of the customer to Product and Engineering, channelling detailed technical feedback from enterprise clients to shape the roadmap

Benefits

• Competitive salary, commission, and meaningful equity in a high-growth start-up
• Clear, accelerated growth opportunities as the company scales rapidly
• Strong in-person culture: 4 days/week in our newly launched North Beach loft office
• Flexible PTO to fully recharge
• 18 paid vacation days in the U.S. plus federal holidays
• Annual learning & development budget
• Comprehensive health, dental, and vision coverage
• Frequent travel opportunities across the U.S., London, and Europe
• Bi-annual company offsites, twice-weekly team lunches, and monthly socials

What This Job Offers

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