Sobre este puesto de Product Designer en Samaya AI
Role
At Samaya, our mission is to move users from information to conviction by delivering insights in a speedy, accurate, auditable, and verifiable manner. We are looking for a Product Designer to help build a product where investment insights become second nature.
This is a high-agency architectural role for a tech-savvy generalist, not a static mockup factory. You will treat the production codebase as one of your canvas, shipping production grade HTML, CSS, and JavaScript next to engineers. We operate on the other side of the AI shift, where tools like Cursor, v0, and Claude unblock designers to act as exponential force multipliers. You will design next-generation paradigms for complex human-AI collaboration, defining how analysts orchestrate multiple autonomous agents, and even rewriting prompt frameworks and system instructions to shape the AI personality.
By building our taste, opinions, and design decisions into the design system, we make it easier for everyone at Samaya to create high-quality work. That gives the design team more time to focus on product architecture, the long-term vision, and the decisions that have lasting impact instead of constantly responding to one-off feature requests or temporary fixes. We make deliberate tradeoffs that let the team move quickly while spending our time on structural improvements that continue to pay off. Over time, this helps the Sundial design language stay consistent and high quality across every touchpoint, from the product UI to presentations, documents, the website, and other brand assets.
Responsibilities
- Shape the user experience, owning what analysts need and how information hierarchy, interaction design, and typography make dense financial data intuitive, fast, and trustworthy
- Architect multi-agent interactions, designing workflows for human collaboration with AI agents and defining how users monitor, direct, and work with multiple agents at once
- Own Samaya AI's persona, shaping how the AI research collaborator thinks, communicates, and behaves so analysts experience it as intuitive, professional, and high integrity
- Ship production code, owning the UI and user experience end to end alongside engineers and product managers, with full accountability for what reaches analysts
- Drive product direction, proposing new concepts, questioning foundational assumptions, and making short-term design decisions that compound toward a clear product vision
- Own the customer loop, running weekly customer calls to hear friction firsthand and translating what you hear into shipped product changes
- Scale the Sundial design language, maintaining cohesion across the product, developing agent-ready skills and a design.md architecture that engineers and AI agents build from, not just a component library
Experience
Required
- 4+ years of professional product design experience with a strong portfolio of shipped digital products
- Hands-on experience writing production code directly in a codebase, with AI tools already central to your daily workflow
- Deep craft across typography, grid systems, color theory, and visual hierarchy, applied consistently across every surface and screen size a product touches
- A proven track record of taking vague, highly underspecified problems and independently carving them into concrete, shippable product features
- Direct experience building, maintaining, or scaling a design system and documenting component libraries and skills for team-wide use
- Experience running user interviews, synthesizing qualitative feedback, and translating customer pain points into shipped product changes that delivered measurable customer and business value
Preferred
- Familiarity with prompt engineering, multi-agent canvases, or interfaces that dynamically adapt to probabilistic AI behaviors
- Background designing for analytical or professional user bases such as financial analysts, researchers, lawyers, or clinicians, where precision and trust matter more than simplicity alone
- A track record building complex dashboards, analytical software, developer tools, or enterprise data platforms
- Experience documenting design patterns, rules, and components specifically optimized for AI agents to interpret and generate interfaces
- A track record extending design thinking across every touchpoint a brand and product meets its audience, with the same rigor and craft applied throughout
Compensation
The cash compensation range for this role is $160,000 - $220,000.
Final offer amounts are determined by multiple factors, including experience and expertise, and may vary from the amounts listed above.
Equity components may also be considered as part of the overall compensation package.
Benefits
Health: Access comprehensive health insurance, including medical, dental, vision, flexible spending account (FSA), and short-term disability.
Wealth: Support for your long-term financial wellbeing with a 401(k) and pre-tax benefits (e.g. commuting).
Rest: Enjoy flexibility to rest and recharge as needed, with unlimited PTO (Paid Time Off).
Flexibility: Work flexibly with a hybrid setup — typically team members spend a minimum of three days in the office per week.
Travel: Grow and connect with a travel budget that encourages conference attendance, customer visits, and team gatherings.
Equipment: Create your ideal workspace with an office equipment allowance to set up what works best for you.
Inclusive Hiring
Interview Accommodations: We are committed to ensuring an equitable selection process for everyone and welcome applicants from varied backgrounds to enrich our team. If you require accommodations or adjustments during our recruitment process, please inform us.
Equal Opportunity Employer: We do not discriminate on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.
Visa Sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. If we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
About Samaya
Samaya builds Expert AI Agents that turn information from the global financial market into investment conviction.
The global financial market is the largest and most valuable information ecosystem in the world, connecting billions of people, influencing every type of productive human activity, and driving tens of trillions of dollars of value. At its core is investment decision-making: identifying areas of productive activity, allocating resources, carried out by millions of people across the globe.
But that process is at a breaking point. The past two decades have brought an exponential increase in market complexity: more information sources, more asset types, more disruptive themes like AI reshaping every corner of the market. For investors, this means exponentially more depth, breadth, and speed required on every decision.
The response is a forced tradeoff: zoom in on a sector or basket of companies and manage the flood, but lose sight of adjacent dynamics that move markets. Or zoom out to track broad themes, but lose the needle-in-a-haystack details that drive precise decisions. No market sector evolves in isolation, and this lack of a simultaneously zoomed-in and zoomed-out picture costs hundreds of billions in missed or suboptimal investment decisions every year.
Samaya was founded to reimagine investment decision-making across the global financial market. General-purpose AI can’t reason about cause and effect across complex economic systems, embed firm-specific context, or execute reliably over long-horizon workflows. We built something different: a purpose-built AI system combining proprietary financial reasoning models, a long-horizon execution engine with persistent memory, and full auditability. Built by a team from Google DeepMind, Meta, Microsoft, and Stanford with 100+ papers and 50k+ citations, it achieves 98% accuracy on financial reasoning tasks where generic LLMs reach 53%. The result is AI that learns how each investor thinks and seamlessly takes them from information to conviction.
Our user base has scaled to 10,000+, with partnerships spanning top financial institutions worldwide, including Morgan Stanley. We’re backed by $43.5M in Series A funding led by NEA, with investors including Eric Schmidt, NVIDIA, Databricks, Yann LeCun, Jeff Dean, Marty Chavez, and Mark Cuban.
Our Operating Principles
Put Users first. Our users rely on us to do their jobs. We exist because our users trust us to help them achieve their goals. In return for this trust users place in us, we keep their needs as our top priority.
Win as a collective. We are high achievers with a drive to succeed. We build strong bonds over this shared drive. We dive in to help when one of us needs it. We’re kind to each other and boost each other to succeed and grow professionally and personally. We build trust with each other by making commitments and consistently delivering on them. This trust means we genuinely support each other, embracing feedback as a tool for growth and improvement. We win by operating this way, as one team.
Focus and iterate quickly. Bias for action makes us build and learn quickly. Iterating fast requires clarity on what outcomes we are targeting and why. Prioritizing the important things, taking full ownership and initiative, making fast initial progress, and rapid iterations lead to the best outcomes.
Innovate Relentlessly. We pursue novel insights, challenging the status quo and reimagining how things are done. We aren’t attached to the past when improving our product and how we work in the future. We actively invest time in innovation, thinking “outside the box” to consistently raise our standards.
Prioritize Outcomes over Egos. We are committed not to a person, an idea, or an opinion but to continuously making progress to our goals. Sometimes, our goals are ambiguous; in those moments, we iterate, learn, and move on to the next inquiry. We ask the tough questions with kindness, dropping our egos in our pursuit of evidence. For our business goals, we learn from our users. For our scientific goals, our understanding is built through rigorous experimentation, research, and observation. For our personal goals, we embrace candid feedback and collaborative learning to guide our progress.
