Senior Solutions Architect - Data Labs
Senior Solutions Architect in Invisible's Data Lab who designs human-data programs for frontier AI clients — translating ambiguous LLM training and evaluation requests into scalable solutions spanning SFT, RLHF, benchmarks, red teaming, and agent environments. Requires deep LLM training/eval knowledge, strong communication, ML/API fluency, and commercial judgment.
- Compensation
- Not disclosed
- Location
- London - Hybrid; New York - Hybrid; San Francisco Bay Area - Hybrid
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Full time
- Experience
- Not specified
- Category
- Architecture
- Posted
Skills
Must have
- Deep, demonstrable interest in how frontier AI models are trained, improved, and evaluated
- Strong working knowledge of LLM training and evaluation concepts, reasoning across data modalities, collection methods, and research objectives
- Exceptional communication skills — listening closely, identifying gaps in underspecified requests, and influencing technical and non-technical stakeholders
- Judgment to challenge assumptions constructively while maintaining momentum and client trust
- Technical fluency in ML, data systems, software architecture, APIs, and data flows
- Commercial judgment and comfort with rough-cut budgeting, weighing research ambition against effort, timeline, cost, and unit economics
- Ability to synthesize client context, research intent, expert capabilities, technical constraints, and operational realities into an executable approach
- Experience working across multiple stakeholders or teams in ambiguous environments
- High ownership, curiosity, adaptability, and low ego
Nice to have
- Background in computer science, software engineering, machine learning, data science, AI research, technical product, or solutions architecture (or equivalent experience)
- Direct experience with human-data programs, data annotation, model post-training, RLHF, RLVR, evaluations, benchmarks, red teaming, or research operations
- Experience partnering directly with AI researchers, research engineers, or technical program managers
- Hands-on ability with Python, SQL, APIs, notebooks, or lightweight prototyping
- Experience designing tools or workflows for specialized users where expert judgment and data quality are central
- Evidence of serious engagement with the field through professional work, research, open-source contributions, technical writing, or independent projects
Full description
About Invisible
Invisible is an Applied AI research company closing the gap between frontier models and the enterprise. We provide the platform infrastructure that makes AI work in production at scale: unify fragmented data, map complex processes, orchestrate and evaluate agents, and stand up hyper-personalized workflow applications fast for companies like Grubhub, Alliance Global, and Thomson Reuters. Where models fall short, we build RL environments and data to fix them. The result: a virtuous cycle between enterprise deployment and model training.
Recognized as Best Predictive Analytics Platform of the Year at the 2026 AI Breakthrough Awards, Invisible makes AI work.
About the Role
Invisible's Data Lab works with leading AI companies to design and deliver the human data that advances model capabilities and measures performance. Our work spans the full frontier of AI training and evaluation—from supervised fine-tuning and preference data to benchmarks, red teaming, multimodal data, coding tasks, and agent environments. Solutions architects are at the center of this work, working with clients to define the problem and translating open-ended model development problems into scalable programs with sound methodology.
We are looking for a Senior Solutions Architect to bring technical depth, sharp commercial judgment, and a strong command of the rapidly evolving AI training and evaluation landscape. Embedded within an account team working with a major frontier AI lab, you will lead solution design for new opportunities and pilots. You will partner with Project Leads who own execution, client management, and overall project outcomes, while remaining accountable for the integrity, feasibility, and scalability of the solution through handoff and early delivery.
You will often enter when a client's ask is still underspecified. Your job is to understand what they are really trying to achieve, translate that into a collection we can execute, and help the client and our teams make the right technical, methodological, and commercial choices. You will connect the perspectives of client researchers, program managers, Project Leads, experts, and engineers—bringing context that may not otherwise exist in the room.
This is not a traditional infrastructure architecture role, nor is it primarily a project management role. It sits at the intersection of ML research, human data, product thinking, and client partnership. Success means teams make better decisions because you are involved: projects are framed correctly, solutions reflect the state of the art, and clients trust Invisible to understand where their work is going next.
You will work across a remarkable range of frontier AI problems, with direct exposure to the researchers and program leaders defining them. You will help determine how novel human-data programs should work before there is an established playbook, influence the products and systems used to deliver them, and build reusable ways of thinking that shape how Invisible approaches the field.