Full-Time
Staff Software Engineer
Network Sourced AI
OpenMined
11-50 employees
Open-source privacy-preserving data access infrastructure
No salary listed
Remote in USA
Remote
Must work within Eastern Time plus or minus one hour.
 Software Engineering (1) |
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- The role requires 8+ years of professional software engineering experience with a track record of personally building, shipping, and operating production systems at meaningful scale.
- Strong Python proficiency is required, including FastAPI, asynchronous patterns, and Docker orchestration.
- Experience with distributed systems and API design is required, including designing and evolving interfaces consumed by multiple independent teams.
- Practical retrieval-augmented generation and information retrieval experience is required, including vector databases, retrieval pipelines, embedding strategies, and aggregation.
- Technical leadership experience demonstrated through introducing engineering quality practices to one or more teams is required.
- The candidate must be comfortable with ambiguity and resource constraints.
- The candidate must be fluent in asynchronous collaboration, have strong written communication, and be able to build high-trust working relationships across a six-hour-or-greater time-zone spread.
- Cross-functional collaboration and communication are required to improve understanding and context sharing between engineers and non-engineering stakeholders.
- The candidate must be located within Eastern Time plus or minus one hour.
- Own the Network Sourced AI squad's technical architecture end to end, aligning design, engineering, and deployment across the stack from current implementation through product roadmap evolution.
- Drive production readiness through deployment monitoring, error handling, graceful degradation, and operational runbooks.
- Establish and demonstrate engineering best-practice norms covering modular system design, security, reliability, scalability, code quality, and production delivery, while mentoring the team.
- Collaborate on core technology-stack strategy through architectural review, identifying components that should become shared organizational primitives, and defining standard interfaces that prevent tight coupling.
- Partner with the product lead to develop and execute realistic roadmaps that balance desired outcomes with feasibility, scalability, and architectural soundness.
- Own delivery of engineering's quarterly goals and ensure consistent, high-impact delivery while managing resources effectively.
- Own team output, delivery, and success, including productivity, timeliness, and morale, by matching team members and work to interests, learning opportunities, capacity, and capability.
- Establish robust tools, processes, and methodologies for high-quality software delivery, while providing hands-on technical leadership through individual development contributions and code reviews.
- Create technical documentation and processes that support high velocity and knowledge transfer.
- Manage a team of 2–4 engineers as a people leader, conduct one-on-ones, provide technical and professional feedback, create professional development plans, and perform performance reviews.
- Experience with Vue 3 and TypeScript, Rust and Tauri, or cross-platform desktop applications is extremely beneficial.
- Networking or peer-to-peer application experience is beneficial.
OpenMined is a non-profit foundation that builds open-source technology infrastructure to help researchers and app developers access data and get answers without copying or directly accessing the data. It maintains Syft, a platform that enables secure, private analysis of non-public information across a public network. The OpenMined community, consisting of over 17,000 technologists, researchers, and industry professionals, contributes code and knowledge to expand data access for scientific fields and industries while protecting data privacy. The goal is to unlock 1000x more data for research and development by providing tools and a collaborative ecosystem that supports private, privacy-preserving data analysis.
Company Size
11-50
Company Stage
N/A
Total Funding
N/A
Headquarters
Oxford, United Kingdom
Founded
2017
Get referred to OpenMined
See people who can refer or advise you
Simplify's Take
What believers are saying
- NIST signed a March 27, 2026 CRADA with OpenMined for secure AI evaluations.
- OpenMined’s July 2026 PySyft release supports remote data science on live datasites.
- Future of Life Institute approved $1,661,750 for OpenMined’s federated infrastructure project.
What critics are saying
- Grantmaking.ai lists $10 million raised, limiting long-term self-funded execution.
- Big labs and NIST can internalize similar evaluation tooling, commoditizing PySyft by 2027.
- If PySyft misses enterprise reliability, OpenMined remains a respected lab, not a durable company.
What makes OpenMined unique
- PySyft lets analysts compute on sensitive data without receiving raw datasets.
- March 2026 CAISI CRADA validates OpenMined’s privacy-preserving evaluation stack.
- OpenMined couples open-source tooling with nonprofit credibility in federal AI standards.
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Benefits
Health Insurance
Flexible Work Hours
Remote Work Options
Unlimited Paid Time Off
Growth & Insights and Company News
6 month growth
↓ -2%1 year growth
↓ -2%2 year growth
↓ -2%CAISI signs frontier AI testing agreements with 3 companies. May 6, 2026 3 mins read The National Institute of Standards and Technology's Center for AI Standards and Innovation, or CAISI, has signed agreements with Google DeepMind, Microsoft and xAI to support frontier artificial intelligence testing and research tied to national security efforts. As government and industry leaders expand efforts to evaluate frontier AI systems for national security applications, discussions around AI's growing role in cybersecurity continue to gain momentum. The 2026 Cyber Summit on May 21 will feature a panel discussion about the role of AI in cyber defense. Reserve your spot now! NIST said Tuesday the agreements build on previously announced partnerships that were renegotiated to align with directives from Commerce Secretary Howard Lutnick and the White House's AI Action Plan. Table of Contents How could CAISI agreements advance AI assessments? According to NIST, the agreements allow government evaluators to assess frontier AI models before public release and conduct additional testing after deployment. CAISI has completed more than 40 evaluations to date, including assessments involving unreleased AI models. Developers frequently provide models with reduced or removed safeguards to support evaluations focused on national security-related capabilities and risks. The agreements also support testing in classified environments and enable participation from evaluators across government agencies through the TRAINS Taskforce, a group of interagency experts focused on AI-related national security issues. CAISI Director Chris Fal said independent measurement science plays an important role in understanding frontier AI and related national security implications. "These expanded industry collaborations help us scale our work in the public interest at a critical moment," Fall added. What is CAISI? CAISI is a component of the Department of Commerce's NIST that serves as industry's primary liaison within the U.S. government to facilitate testing, collaborative research and development of best practices related to commercial AI tools. In March, CAISI teamed up with the nonprofit OpenMined to develop methods for evaluating AI systems while preserving data confidentiality. It also partnered with the General Services Administration to establish approaches to AI systems evaluation.
NIST's CAISI collaborates with OpenMined to develop privacy-preserving methods for AI evaluations. March 30, 2026 3 mins read The National Institute of Standards and Technology's Center for AI Standards and Innovation is teaming up with the nonprofit OpenMined to develop methods for evaluating artificial intelligence systems while preserving data confidentiality. The organizations signed a collaborative research and development agreement to utilize OpenMined's software infrastructure, including PySyft, to enable AI evaluations that adhere to security requirements and maintain scientific rigor, NIST said Friday. PySyft enables researchers to perform data science and analysis using non-public information without seeing or obtaining a copy of sensitive datasets. Balancing innovation and modernization with security as agencies increase adoption of AI will be a key topic at the Potomac Officers Club's 2026 Digital Transformation Summit, happening on April 22. The event will bring together government and industry leaders to explore how agencies are integrating AI into high-security federal environments to support various missions. Sign up today to gain insights from the figures shaping federal digital transformation. Table of Contents How is the caisi-openmined partnership intended to improve AI evaluations? By developing privacy-preserving evaluation methods, stakeholders can conduct rigorous AI evaluations to measure system performance even when underlying data, models or benchmarks cannot be shared due to intellectual property, data protection or national security constraints. According to NIST, insights from the effort will inform the agency's development of voluntary standards, best practices and recommendations for AI evaluation. The partnership builds on CAISI's prior work with the General Services Administration to provide evaluation frameworks, testing methodologies, and performance measurement tools for agencies before and after deployment in support of USAi, a governmentwide platform that accelerates agency adoption of generative AI. What is CAISI? The National Institute of Standards and Technology's Center for AI Standards and Innovation, or CAISI, serves as the U.S. government's primary interface with industry for testing and collaborative research on commercial AI systems. The organization works with federal partners to develop guidelines to improve AI security. It also evaluates AI capabilities that may pose risks to national security. The center recently launched the AI Agent Standards Initiative to promote secure, interoperable and trustworthy autonomous AI systems. Under the initiative, CAISI aims to develop industry-led AI agent standards, support community-driven open-source protocols, address security risks associated with agentic AI, and reinforce U.S. leadership in international AI governance.
Announcement: CAISI signs CRADA with OpenMined to enable secure AI evaluations. March 27, 2026 The Center for AI Standards and Innovation (CAISI) has signed a collaborative research and development agreement (CRADA) with OpenMined, a 501(c)(3) non-profit that develops open-source software infrastructure for secure computation across organizational boundaries. Under this agreement, CAISI and OpenMined will collaborate on research into privacy-preserving methods for conducting AI evaluations, enabling rigorous measurement of AI systems even when the underlying data, models, or benchmarks must remain confidential due to, for example, intellectual property concerns, data protection requirements, or national security considerations. Access to real-world or sensitive data presents a challenge for researchers as AI evaluations are increasingly intended to reflect or predict real-world deployments. It is simultaneously crucial that data is shared in a secure and decentralized manner, in order to safeguard intellectual property, encourage innovation, and maintain privacy. This collaboration will leverage OpenMined's software infrastructure, including PySyft and subsequent advances, to conduct evaluations that address both the security requirements of AI developers and data owners, as well as the scientific rigor demanded by researchers and evaluators. The insights generated from this collaboration will support NIST's efforts in AI security and applied AI evaluation. This research will inform the development of voluntary standards, best practices, and future recommendations for AI practitioners and adopters on how to effectively measure AI systems, e.g., for workforce or productivity uplift and other impacts. Released March 27, 2026
OpenMined introduces “Remote Data Science” as it believes it is the future of private data science.
Today, OpenMined is proud to announce the Beta version of a framework for differential privacy in Python OpenMined call PipelineDP, which OpenMined built in tight collaboration with Google.