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New York, New York, United States
Onsite
Valthos Inc.
Valthos is an applied biological intelligence company. We build and deploy software and biological AI systems to safeguard humanity.
The same AI architectures that enable self-driving cars, land rockets with precision, and deliver expert-level reasoning are beginning to be deployed in biological design. To stay ahead, we must advance our arsenal of tools to capture and design against real-time sensitivities in nature’s evolving mutational landscape.
We are a group of mission-driven software engineers from Palantir and applied biological ML engineers from MIT’s Broad Institute and DeepMind making the latest advances in computational biology accessible in the real world for federal and commercial use.
Grove is Valthos’s product for making complex biological data useful in real-world missions. It combines sequencing and contextual data with computational methods, models, and reference sources to help users identify and characterize biological threats, understand the evidence behind a result, and determine what to do next.
Today, those capabilities are fragmented across instruments, custom pipelines, databases, and specialist teams. Grove brings them into a coherent product. Ingesting and processing data, coordinating biological methods, preserving lineage, and presenting findings in a form people can understand and use. It is designed to evolve as models, methods, and reference data change, and to operate in customer-controlled environments that may be disconnected, bandwidth-limited, compute-limited, or classified.
A product engineer at Valthos owns core parts of Grove from an ambiguous customer need through production software. The role works directly with customers, computational biologists, AI engineers, founders, and mission partners to understand hard problems and build the product capabilities that address them.
This is a broad full-stack role spanning interfaces, APIs, services, data models, computational workflows, integrations, and deployment infrastructure. There is no handoff between defining the product and building it. The person who thrives here combines strong engineering with product judgment. Learning enough of a difficult domain to make good decisions, identifying the right abstraction without overbuilding it, and shipping quickly without leaving behind a fragile system.
Own core product capabilities from the initial customer problem through product definition, architecture, implementation, deployment, and iteration
Work directly with customers, business development, and domain experts to understand mission needs and translate complex technical workflows into clear product behavior
Build across the application stack, including user-facing interfaces, APIs, backend services, data models, computational workflows, integrations, and infrastructure
Turn models, biological methods, and reference sources into reliable, versioned, and testable product capabilities
Design workflows that preserve source data, supporting evidence, provenance, uncertainty, and clear opportunities for user review
Build product experiences, visualizations, reports, alerts, and integrations that make technical findings understandable and useful
Prototype with customers and representative data, determine what works, and turn proven needs into durable capabilities and shared product primitives
Define end-to-end evaluations that test whether the complete product works under realistic data, deployment, and time constraints
Make pragmatic decisions about scope, sequencing, architecture, and build versus buy while owning the reliability, performance, security, and maintainability of software in production
Experience independently owning substantial product capabilities or applications from an ambiguous problem through production and subsequent iteration
Strong full-stack engineering ability, with depth in at least one area and the ability to work effectively across interfaces, backend services, data, and infrastructure
Experience building production applications with React and TypeScript and backend systems with Python or comparable languages and frameworks
Strong understanding of API design, data modeling, relational databases, asynchronous workflows, and production systems
Ability to translate complex or partially understood technical workflows into clear, durable software
Strong product judgment, including direct customer engagement, effective scoping, and the ability to identify the underlying problem behind a feature request
Systems thinking paired with practical restraint. Knowing when to create a reusable primitive and when a purpose-built solution is sufficient
Ability to learn unfamiliar technical domains quickly and work effectively with researchers, customers, designers, and engineers
Comfort working on sensitive biological and national-security problems with discretion and good judgment
Experience building scientific, intelligence, public-health, enterprise, or other data-intensive software
Experience with workflow orchestration, data pipelines, asynchronous processing, distributed systems, or containerized CPU- and GPU-based workloads
Experience integrating changing models, computational methods, or reference data into production systems
Experience building maps, timelines, graphs, evidence views, or other interfaces for exploring complex information
Experience evaluating complete workflows or products rather than relying solely on model-level benchmarks
Experience building software for secure, regulated, on-premises, edge, disconnected, or air-gapped environments
Experience using AI-assisted development tools while maintaining judgment and ownership over the resulting system
Background in or exposure to computational biology, bioinformatics, biodefense, public health, or national security
If there is a fit, we will schedule behavioral and technical interviews. The final step is an onsite in our office, where candidates work on a small project, discuss ideas, and collaborate with the wider team.
