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Valkai

Agent platform for pharma and device workflows

Member of Technical Staff - Product Engineering

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • Start with the user's problem and care whether the experience is clear, useful, and trustworthy.
  • Maintain a high bar for interaction details, performance, accessibility, and code quality.
  • Move between frontend, backend, data, and AI systems to ship a complete product.
  • Simplify complex capabilities without hiding important controls or failure modes.
  • Turn unclear workflows into a concrete product direction and move them forward.
  • Collaborate with product, design, AI Strategy, and AI engineers and communicate tradeoffs clearly.

Responsibilities

  • Build assistant experiences across web and document-based workflows.
  • Design product patterns for scheduled work, durable agent runs, approvals, progress, and recovery.
  • Build reusable workflow and prompt libraries that help users get consistent results.
  • Create clear controls, feedback loops, and explanations for complex agent behavior.
  • Connect product telemetry and evaluations so the team can measure and improve quality.
  • Work across the frontend and backend stack to ship complete, reliable features.
  • Partner with product, AI Strategy, and AI engineers from problem discovery through launch and iteration.

Desired Qualifications

  • Ship user-facing products from early concept through production.
  • Build complex interactive applications with React and TypeScript.
  • Design interfaces for agents, AI systems, or other probabilistic software.
  • Work closely with enterprise users on workflow-heavy products.
  • Work in a high-growth early-stage company.
  • Be familiar with parts of the stack: Next.js, TypeScript, Python, Postgres, Azure, and AWS.

About the Company

Valkai

Agent platform for pharma and device workflows

Valkai builds an agent orchestration layer for pharmaceutical, biotech, and medical device companies, connecting the siloed systems, teams, and outside data that make development slow. Its agents run on an organization's own SOPs, precedents, and regulatory context, draw on more than 100 data sources, and execute multi-step workflows that end in review-ready documents with citations, covering everything from discovery through commercialization. The company says more than 200 agent systems coordinate work across those stages, and it deploys through private cloud or managed SaaS. Unlike a general-purpose assistant, the agents are bound to the procedures and evidence standards a regulated submission requires. The company's goal is to compress work that currently takes months into weeks by removing the handoffs between systems.

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