SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.
We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.
At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.
This is not a typical backend engineering position, but a founding opportunity to define the architecture, culture, and values of a frontier agentic AI platform. As the first backend engineering hire on our Agentic AI team, you will shape and build the systems that allow intelligent agents to autonomously execute complex scientific workflows, interact with real-world systems, and learn over time. You’ll be working with a team of world-class scientists and engineers in a high-talent, no-ego environment.
We are seeking someone who is both a high-agency builder and a reflective technologist and a person who can write beautiful, scalable code and pause to ask: What are the long-term consequences of these architectural decisions?
As an ideal candidate, you are obsessed with data and have experience building observability and metrics into and around the software you’re writing. You are a great communicator, who uses this data to demonstrate the impact of the software you’re writing and influence its adoption. You’ll bring broad experience in CI/CD, infrastructure as code, API design, application code, and databases. Most importantly, you’ll bring a track record of working in a small, fast-moving software development team, exploring new technologies, and solving problems across an entire software stack. Experience in designing, building, and deploying AI systems, especially in LLMs and agentic systems (multi-agent orchestration, autonomous workflow engines, or goal-oriented agents) is a bonus.
What You’ll Do- Architect and implement intelligent agents and multi-agent orchestration systems that enable goal-driven automation in scientific research.
- Design and build APIs, workflows, and systems that interface with simulations, ML models, third-party tools, and other agents, all while ensuring transparency and safety in their behaviors.
- Champion observability, traceability, and reliability making sure every line of code is measurable and maintainable.
- Collaborate with AI researchers and domain scientists to prototype agent behaviors in real-world pipelines, and evolve prototypes into robust production systems.
- Drive internal engineering standards, infrastructure decisions, and deployment best practices for a research-informed and ethically grounded development process.
- Contribute to the broader AI and scientific software community through open-source contributions, publications, or educational initiatives, as time allows.
- You are an engineering leader (formally or informally) who thrives on turning nascent ideas into working software that scales.
- You are deeply curious about intelligent systems, and how to make them interpretable, auditable, and aligned with human intent.
- 5+ years of professional software development experience, ideally with Python as a primary language.
- Experience building complex distributed systems, RESTful APIs, and performant backend services.
- Proficient in data modeling, query optimization, and have worked with relational and graph databases.
- Strong foundation in DevOps, CI/CD, and infrastructure-as-code practices (e.g., Terraform, Docker, GCP preferred).
- Familiarity with agentic AI frameworks (e.g., LangGraph, CrewAI, AutoGen) or orchestration patterns for multi-agent systems.
- Strong communication and collaboration skills able to translate abstract requirements into architecture, and architecture into code.
- Passionate about building responsibly, you think critically about failure modes, edge cases, and ethical implications of autonomous systems.
- Previous experience in agentic system design, reinforcement learning, or LLMs.
- Exposure to biotech, chemistry, or simulation domains, or scientific computing environments.
- Contributions to open-source, publications in AI ethics or human-AI collaboration, or involvement in standards development.
SandboxAQ offers the rare combination of startup energy, scientific ambition, and mission-driven impact. Here, your work will contribute to platforms used by world-class researchers, government institutions, and scientific labs, accelerating discovery in ways that matter. You’ll shape the foundation of how agentic AI evolves in high-stakes environments—and help ensure it evolves wisely.
The US base salary range for this full-time position is expected to be $183K - $256K per year. Our salary ranges are determined by role and level. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.
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