Full-Time

Senior Software Engineer

Backend Systems

Valency

Valency

11-50 employees

Trusted AI reasoning infrastructure for science

No salary listed

Berkeley, CA, USA

Hybrid

Three days on-site per week required.

Category
Software Engineering (1)
Required Skills
RabbitMQ
Kubernetes
DynamoDB
Rust
Microsoft Azure
Python
Airflow
Distributed Systems
MySQL
Node.js
Product Management
Apache Kafka
Java
Postgres
Data Engineering
Docker
TypeScript
SOC 2
AWS
Go
Terraform
Redis
MongoDB
REST APIs
DevOps
OAuth
Google Cloud Platform

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Requirements
  • At least 8 years of software engineering experience with deep expertise in backend systems, including APIs, databases, distributed architectures, and cloud infrastructure.
  • Strong command of at least one backend language such as Python, Go, Java, or Rust, and comfort working across AWS, Google Cloud Platform, or Azure.
  • Hands-on experience with relational databases, including schema design, query optimization, and indexing, plus familiarity with non-relational or caching layers.
  • Experience with containerization and orchestration using Docker and Kubernetes, and with continuous integration and continuous delivery pipelines.
  • Demonstrated ability to own and deliver complex, ambiguous projects end-to-end with minimal supervision.
  • A track record of mentoring engineers and influencing technical direction without formal authority.
  • Candidates must be legally authorized to work in the United States.
Responsibilities
  • Design, build, and own critical backend services, including APIs, data pipelines, asynchronous workers, and the infrastructure required to run them reliably at scale.
  • Make architectural decisions and document trade-offs clearly.
  • Drive platform and reliability investments alongside feature work.
  • Establish and uphold standards for code quality, test coverage, and operational excellence.
  • Diagnose and resolve complex performance, reliability, and scalability issues, and conduct post-mortems to prevent recurrence.
  • Design and maintain distributed systems resilient to failure, applying circuit breakers, retries, idempotency, and rate limiting where appropriate.
  • Own the full lifecycle of services from design through deployment, including continuous integration and continuous delivery pipelines, containerization with Docker and Kubernetes, and cloud infrastructure.
  • Implement and improve observability practices including structured logging, metrics dashboards, distributed tracing, and alerting.
  • Contribute to infrastructure-as-code practices using Terraform, Pulumi, or similar tools, and optimize cloud costs.
  • Design performant, well-normalized data models across PostgreSQL, MySQL, Redis, MongoDB, and DynamoDB.
  • Build and maintain data pipelines, extract-transform-load and extract-load-transform workflows, and integrations with third-party services and external APIs.
  • Apply CDN, in-memory, and application-level caching strategies and understand their failure modes.
  • Work with Kafka, SQS, and RabbitMQ message queues and event-streaming platforms to build decoupled asynchronous architectures.
  • Apply secure coding practices including input validation, secrets management, least-privilege access, and protection against common vulnerabilities.
  • Contribute to SOC 2, GDPR, or similar compliance efforts with attention to data privacy and auditability.
  • Unblock teammates, provide technical direction, and raise the quality of design reviews.
  • Mentor junior and mid-level engineers through code review, pairing, and direct constructive feedback.
  • Write architecture decision records and technical documentation.
  • Partner with Product and Design to scope work, surface constraints, and deliver clearly.
  • Represent engineering in cross-functional conversations.
Desired Qualifications
  • Experience working in a startup environment, building and scaling systems while the business grows rapidly, wearing multiple hats, and thriving in ambiguity.
  • Experience with Node.js, TypeScript, AWS Lambda, AWS CDK, Step Functions, PostgreSQL, or Cloudflare.
  • Familiarity with authentication systems such as OAuth and observability tooling.
  • Experience with workflow orchestration tools such as Temporal, Airflow, or Prefect and asynchronous job processing at scale.
  • Working knowledge of infrastructure-as-code tools such as Terraform or Pulumi and cloud cost management.

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 Jobs

Simplify's Take

What believers are saying

  • July 2026 Genesis funding gives Valency a government-backed wedge into nuclear research.
  • Berkeley Lab's HERALD project showcases Valency on auditable, high-stakes scientific workflows.
  • August 2026 hiring for product leadership signals active expansion beyond a single pilot.

What critics are saying

  • Valency lacks disclosed revenue, so DOE pilot success must convert into paid contracts fast.
  • July 2026 HERALD becomes a reference customer test; failure blocks national-lab expansion.
  • Competing research-infrastructure platforms from Google, Anthropic, and OpenAI can replicate MCP workflows.

What makes Valency unique

  • July 22, 2026 DOE Genesis selection validates Valency's auditable AI infrastructure.
  • Valency Bond indexes 450+ million papers and preprints within hours of posting.
  • Valency natively supports Model Context Protocol across 38 tools through one endpoint.

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Benefits

Hybrid Work Options

Remote Work Options

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

-11%

1 year growth

-11%

2 year growth

-11%
PR Newswire
Jul 22nd, 2026
Valency selected for DOE Genesis Mission to accelerate nuclear power research with AI agents

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.