GTM Engineer
About the job
- Production-quality coding ability in Python, TypeScript, or a similar language, with the ability to build demos and integrations from scratch quickly.
- Experience at the intersection of engineering and go-to-market, such as sales engineering, developer relations, technical marketing, or an early technical startup role.
- Ability to communicate with research engineers at national laboratories and enterprise buyers and translate between them.
- Ability to work effectively in an ambiguous environment without an established playbook.
- Legal authorization to work in the United States.
- Build and maintain technical demos, sample integrations, and proof-of-concept environments that showcase the platform's MCP-first capabilities to prospects and partners.
- Build and develop landing pages and measure their success.
- Own technical content, including integration guides, code samples, and tutorials, to shorten time-to-first-value for new users and evaluators.
- Support sales and solutions engineering on technical evaluations, proof-of-concepts, and requests for proposals with national laboratories and enterprise research teams.
- Build lightweight internal tooling to instrument and report go-to-market metrics, including activation, usage, and pipeline funnel metrics.
- Partner with product and engineering to translate the roadmap into go-to-market-ready technical narratives and enablement materials.
- Represent the company in developer and research-computing communities through GitHub, Discord, and technical forums by answering questions, contributing examples, and feeding field insight back to product.
- Prototype and test product-led-growth mechanics, including self-serve onboarding flows and in-product activation nudges.
- Provide code written for demos, integrations, or developer tooling as work samples.
- Provide technical content created for users, such as documentation, tutorials, or sample applications.
- Provide examples of working directly with sales or customers on technical evaluations.
- Familiarity with Attio.
- Understanding of application programming interface-first, developer-facing products.
- Exposure to Model Context Protocol or similar agentic/artificial-intelligence tooling.
- Familiarity with academic publishing or research infrastructure.
- Hands-on experience building or consuming Model Context Protocol servers.
- A scientific or research background.
- Prior startup experience in a build-it-from-scratch environment.
About the company
Valency provides a trusted research infrastructure that grounds AI reasoning in real scientific literature, addressing hallucinations from large language models. Its Valency Bond connects with LLMs and next-generation tools to create a grounded reasoning workflow for researchers. Unlike general AI platforms, Valency focuses on integrating credible, up-to-date research content to accelerate discovery for the 35 million researchers worldwide. The product works by linking LLMs with a framework and tools that rely on real research data, enabling researchers to enhance reasoning, verify results, and streamline scientific workflows. The company differentiates itself by offering a grounded, research-backed ecosystem and infrastructure designed specifically to support scientific inquiry, aiming to speed up discoveries and improve trust in AI-assisted research.
Company Size
11-50
Company Stage
N/A
Total Funding
N/A
Headquarters
Berkeley, California
Founded
2026
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Simplify's Take
What believers are saying
- July 22, 2026 Genesis Mission selection gives Valency federal validation and budgeted demand.
- August 2026 job postings for product, growth, and research roles signal active scaling.
- Valency's public corpus reaches 450+ million documents, a moat for scientific search.
What critics are saying
- Genesis is the first real-world use; commercial revenue remains unproven.
- Javelin's August 1, 2026 posting says Valency has almost no data infrastructure.
- If scientists ignore provenance-heavy tools, Valency's entire agentic-science thesis collapses.
What makes Valency unique
- Valency Bond indexed 450+ million papers and preprints, with citations traceable within hours.
- Its MCP-native infrastructure powers audited AI agents for DOE-backed HERALD research.
- CEO Josh Bloom and COO Ryan Anderson pair Berkeley science with enterprise execution.
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Benefits
Hybrid Work Options
Remote Work Options
Company Equity
401(k) Company Match
Growth & Insights and Company News
6 month growth
20%1 year growth
20%2 year growth
20%Valency has been selected for the US Department of Energy's Genesis Mission to accelerate nuclear power research using AI agents. The company will partner with Lawrence Berkeley National Laboratory on the HERALD project, led by scientists Daniela Ushizima and Peter Nugent. HERALD aims to deploy AI agents to review vast archives of nuclear power research, allowing human security experts to focus on critical judgment calls. Valency will provide the AI agent infrastructure to support hundreds of millions of scientific documents whilst maintaining auditable chains of custody required for DOE compliance. The system uses the Model Context Protocol natively, enabling AI agents to work across the archive whilst keeping human experts in control of final decisions. Valency specialises in foundational infrastructure for AI-accelerated science.