TavilyRemote · London, United Kingdom; Remote - Europe
EncordPosted 2mo ago
Solutions Engineer at Encord scores 75 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
About us
Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production.
Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator.
The role
As a Solutions Engineer at Encord, you will be the core technical expert and problem-solver for our most complex customers. You are the engineering-focused counterpart to the commercial team, partnering with Account Executives to architect and implement solutions for prospects on the cutting-edge of AI.
You will be the expert on how our platform integrates and scales, establishing technical credibility and guiding prospects through complex evaluations, especially for applications in robotics, autonomous systems, and multimodal AI. You are both a deep technical builder and an expert business value translator.
What you'll do
Partner with Account Executives and the ML team to lead the technical strategy for complex, enterprise sales cycles and co-own the technical win
Lead deep technical discovery sessions with a wide range of stakeholders (from ML Engineers to MLOps leaders) to not only uncover business pain but to architect a complete technical solution and integration path
Architect, build, and deliver highly-technical, customised product demonstrations and proof-of-concepts (POCs) that solve specific, complex customer problems
Own the end-to-end technical implementation of POCs, writing robust, production-quality Python scripts for complex data ingestion, pre/post-processing, dataset management, and custom platform integrations
Act as the key technical advisor to prospects, expertly guiding them through security, architecture, and integration evaluations, particularly on complex data pipelines involving multimodal data, LiDAR, or robotics sensor data
Translate complex technical architectures and findings into clear, persuasive value propositions for senior, non-technical stakeholders (Directors, VPs, CTOs)
Serve as the "voice of the customer" to our Product and Engineering teams, channelling detailed, technical feedback from complex enterprise clients to help shape the product roadmap
Who we're looking for
Coding experience — hands-on experience building and debugging scripts and solutions using Python or other scripting languages; experience with SDKs is desirable
Excellent communication and presentation skills — you can confidently command a room of engineers and just as easily simplify complex concepts for senior decision-makers
Strong technical command of modern cloud infrastructure (GCP, AWS, Azure) and machine learning concepts
A "hacker mindset" with a strong engineering foundation: you are a creative problem-solver who builds robust, scalable, and efficient scripts and integration workflows to overcome technical hurdles
A solution-driven and customer-obsessed mindset — while you understand commercial goals, your passion is for solving complex technical problems and ensuring customer success
Ability to translate value between technical and commercial stakeholders, both with prospects and internally within Encord
Bonus: hands-on experience working with multimodal AI, sensor-fusion, physical AI, LiDAR data, or in the robotics industry
Experience requirements
1 - 5+ years of experience in a customer-facing role within an AI business, such as Solutions Engineering, Solutions Architecture, or Technical Account Management
Proficiency in Python, with the ability to write clean, production-quality scripts for data ingestion, pipeline automation, API integrations, and custom tooling; experience with REST APIs and SDKs is strongly preferred
Hands-on experience with at least one major cloud platform (GCP, AWS, or Azure), including data storage, compute, and deployment patterns common in ML workflows
Solid understanding of machine learning concepts and the ML development lifecycle — from data preparation and annotation through model training, evaluation, and deployment
Demonstrated ability to lead technical discovery, architect integration solutions, and own end-to-end POC delivery in a complex enterprise sales environment
Proven track record of earning trust with highly technical audiences (ML engineers, MLOps, data engineers) while communicating value clearly to senior business stakeholders
Experience navigating enterprise security, compliance, and architecture reviews as part of a technical sales or implementation process
Prior experience in a high-growth start-up or scale-up strongly preferred
Bonus: Familiarity with multimodal data formats, LiDAR, robotics sensor data, or physical AI applications
Why Encord
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
Flexible PTO to fully recharge
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
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: Ml Ops. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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