About

Edison Scientific builds and commercializes AI agents for science. Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that. We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.

Role

As a Forward Deployed Engineer, you'll be embedded directly with one of the world's leading science R&D organizations – taking full ownership of how Edison's AI agents create value in their environment. You'll need to deeply understand their science, their workflows, and their pain points, then determine where our platform can have the most impact.

This isn't remote support or implementation consulting. You'll be on-site, building relationships with scientists and research leaders, identifying the highest-leverage problems, and shipping solutions in fast cycles – often end-to-end. You'll operate with a high degree of independence and serve as the bridge between what our platform can do and what the customer needs it to do, feeding insights back to our product and engineering teams to shape the roadmap.

Responsibilities

• Be embedded at a client site, understand their research workflows deeply, and take responsibility for maximizing the value Edison delivers to that organization.
• Map the customer's scientific and operational landscape to identify where AI agents can have the most impact – not just where they ask for help, but where the real leverage is.
• Design, implement, and iterate on production-ready integrations in fast cycles, often owning features end-to-end from architecture to rollout.
• Troubleshoot issues in real time, ensure reliability and adoption, and be the go-to technical contact for AI within the client organization.
• Capture pain points, unmet needs, and product gaps and work with our internal Applied AI and engineering teams to shape future capabilities.

Qualifications

• 4+ years of professional software engineering experience, with a track record of shipping production-grade software in fast-paced or ambiguous environments.
• Comfortable operating independently, making decisions with incomplete information, and driving outcomes without close oversight.
• Strong problem-solving skills and comfort navigating complex systems, debugging issues in real time, and owning features end-to-end.
• Proficiency in Python and/or TypeScript/JavaScript.
• Strong communication and relationship-building skills – able to earn trust with scientists, executives, and engineering teams.
• Willingness to learn new scientific domains quickly and adapt to rapidly evolving priorities.

Bonus points for:

• Experience in life sciences, pharma, biotech, or scientific R&D – either as a researcher, consultant, or engineer working in these environments.
• Experience working with AI/ML systems, LLM-powered applications, or agent architectures.
• Background as a technical founder, forward-deployed engineer, or management consultant.
• A science degree or research experience alongside your engineering skills.

Compensation

• $200,000 - $350,000  •  Offers equity

Why join us?

• Competitive salary and equity
• Full healthcare coverage — we pay 100% of premiums for you and your dependents
• Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot
• 401(k) company matching
• $300 health and wellness benefit
• Lunch is on us every day you're in the office, and dinner is on us when you're working late
• Regular team offsites and company events
• A fast-moving, mission-driven culture where smart people do their best work and actually enjoy doing it

About

Edison Scientific builds and commercializes AI agents for science. Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that. We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.

Role

As a Principal Platform Engineer, you'll play a key role in designing, scaling, and operating the core platform infrastructure that powers autonomous scientific discovery. Your primary focus will be the orchestration for our agents at scale — building and managing clusters that orchestrate thousands of persistent, stateful workloads, developing custom resource definitions (CRDs) and operators, and ensuring the reliability and efficiency of our compute layer at scale.

Our mission is to build an AI scientist, and you'll own the infrastructure foundation it runs on. AI agents performing long-running scientific research demand resilient scheduling, lifecycle management, and resource orchestration far beyond typical cloud-native workloads. This role will influence platform architecture, establish infrastructure best practices, and partner closely with backend engineers, ML engineers, and researchers to deliver a production-grade environment that lets science move faster.

At Edison Scientific, engineering at the senior level is about technical ownership and leverage- understanding how complex systems interact, making sound architectural tradeoffs, and building foundations that allow teams and science to move faster.

This role is on-site at our San Francisco office in the Dogpatch neighborhood. Our office is a converted warehouse with high ceilings, open space, and a team that genuinely believes in what they're building.

This position is part of the Platform team. 

Responsibilities

• Architect, implement, and operate Kubernetes clusters that support thousands of concurrent, persistent resources (agents, jobs, services) with high availability and efficient resource utilization.
• Design and develop custom resource definitions (CRDs) and Kubernetes operators to model and manage domain-specific workloads such as AI agent lifecycles, research pipelines, and long-running compute tasks.
• Drive the strategy for cluster scaling, node pool management, autoscaling policies, and resource quota frameworks to handle rapid workload growth.
• Build and maintain infrastructure-as-code (Terraform, Pulumi, or similar) for reproducible, version-controlled environment management.
• Design and implement robust scheduling, placement, and affinity strategies to optimize cost, performance, and fault tolerance for heterogeneous workloads (CPU, GPU, memory-intensive).
• Establish and uphold best practices around observability, monitoring, alerting, and incident response for infrastructure systems (Prometheus, Grafana, Datadog, or similar).
• Own storage and networking strategy within Kubernetes — including persistent volume management, CSI drivers, service mesh, network policies, and ingress architecture.
• Troubleshoot complex, cross-system infrastructure issues and guide others through effective debugging and remediation in distributed environments.
• Collaborate closely with backend, ML, and research teams to understand workload requirements and translate them into reliable infrastructure patterns.

Qualifications

• 5+ years of professional infrastructure or platform engineering experience, with deep hands-on Kubernetes expertise in production environments.
• Experience designing and implementing custom resource definitions (CRDs) and Kubernetes operators (using frameworks such as Kubebuilder, Operator SDK, or controller-runtime).
• Track record of operating and scaling Kubernetes clusters supporting thousands of persistent or long-lived resources (stateful workloads, persistent pods, long-running jobs).
• Deep understanding of Kubernetes internals — API server, etcd, scheduler, controller manager, kubelet — and how they behave at scale.
• Expertise with cloud infrastructure (AWS EKS, GCP GKE, or Azure AKS) and associated networking, storage, and IAM primitives.
• Proficiency in at least one systems or backend language for operator development and infrastructure tooling.
• Hands-on experience with infrastructure-as-code tools (Terraform, Pulumi, or Crossplane) and GitOps workflows.
• Strong working knowledge of container networking (CNI plugins, service mesh, network policies), storage (CSI, persistent volumes, StatefulSets), and security (RBAC, Pod Security Standards, secrets management).
• Ability to operate autonomously, make sound technical judgments, and drive projects from concept through production.

Bonus points for:

• Experience with data-intensive platforms, scientific computing, or ML/AI infrastructure.
• Prior experience in startups or small teams with significant architectural ownership and ambiguity.
• Experience scaling systems, teams, or platforms through periods of rapid growth.

Salary

$200,000 - $350,000  •  Offers equity

Why join us?

• Competitive salary and equity
• Full healthcare coverage — we pay 100% of premiums for you and your dependents
• Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot
• 401(k) company matching
• $300 health and wellness benefit
• Lunch is on us every day you're in the office, and dinner is on us when you're working late
• Regular team offsites and company events
• A fast-moving, mission-driven culture where smart people do their best work and actually enjoy doing it

About

Edison Scientific builds and commercializes AI agents for science. Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that. We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.

Role

As a Principal Full-Stack Engineer (Backend-Focused) you’ll play a key role in shaping and scaling our core platform that automates scientific discovery. You’ll work across the stack, with a strong emphasis on backend systems- designing and evolving services, APIs, data pipelines, and infrastructure- while also contributing to critical user-facing workflows.

Our mission is to build an AI scientist, and you’ll help define and build the tools, interfaces, and data systems it relies on. This role goes beyond implementation: you’ll influence architectural direction, establish engineering best practices, and partner closely with frontend engineers, designers, and researchers to deliver robust, end-to-end solutions.

At Edison Scientific, full-stack engineering at the senior level is about technical ownership and leverage- understanding how complex systems interact, making sound architectural tradeoffs, and building foundations that allow teams and science to move faster.

This role is on-site at our San Francisco office in the Dogpatch neighborhood. Our office is a converted warehouse with high ceilings, open space, and a team that genuinely believes in what they're building.

This position is part of the Platform team. 

Responsibilities

• Architect, design, implement, and maintain backend services, APIs, and databases that power the scientific discovery platform.
• Drive technical decisions across the stack, balancing scalability, reliability, security, and developer velocity.
• Lead the design and evolution of data pipelines supporting AI agents and research workflows.
• Contribute to and review frontend features and workflows, ensuring seamless integration with backend systems.
• Establish and uphold best practices around testing, monitoring, observability, and incident response.
• Troubleshoot complex, cross-system issues and guide others through effective debugging and remediation.
• Collaborate closely with engineering, design, and research teams to scope, plan, and ship new AI-driven capabilities.
• Mentor and support other engineers, raising the technical bar and fostering a strong engineering culture.
• Act as a trusted technical partner in a highly collaborative team working at the frontier of AI for science.

Qualifications

• 5+ years of professional software engineering experience, with significant experience across backend systems and full-stack development.
• Deep proficiency in one or more backend languages (e.g., Python, Node.js), with a strong track record of designing production systems.
• Extensive experience designing, building, and evolving APIs (FastAPI, REST; GraphQL a plus).
• Strong working knowledge of modern frontend frameworks (e.g., React, Next.js) and how frontend and backend systems interact at scale.
• Expertise with relational and/or document databases (PostgreSQL, MySQL, MongoDB, or similar), including schema design and performance considerations.
• Hands-on experience with cloud infrastructure (AWS, GCP, or Azure) and containerized environments (Docker; Kubernetes preferred).
• Proven experience building and maintaining CI/CD pipelines, automated testing strategies, and observability systems.
• Ability to operate autonomously, make sound technical judgments, and drive projects from concept through production.
• Strong communication skills and experience collaborating across disciplines in fast-moving environments.

Bonus points for

• Experience with data-intensive platforms, scientific computing, or ML/AI infrastructure.
• Prior experience in startups or small teams with significant architectural ownership and ambiguity.
• Experience scaling systems, teams, or platforms through periods of rapid growth.

Salary

$200,000- $350,000  •  Offers equity

Why join us?

• Competitive salary and equity
• Full healthcare coverage — we pay 100% of premiums for you and your dependents
• Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot
• 401(k) company matching
• $300 health and wellness benefit
• Lunch is on us every day you're in the office, and dinner is on us when you're working late
• Regular team offsites and company events
• A fast-moving, mission-driven culture where smart people do their best work and actually enjoy doing it

About

Edison Scientific builds and commercializes AI agents for science. Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that. We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.

Role

As a Frontend Engineer, you will help build our “integrated research environment” and design a UX that empowers scientists to integrate AI into their discovery process.

This role is on-site at our San Francisco office in the Dogpatch neighborhood. Our office is a converted warehouse with high ceilings, open space, and a team that genuinely believes in what they're building.

This position is part of the Platform team. 

Responsibilities

• Architect, design, implement, and optimize the front-end for our scientific discovery platform with a focus on performance and scalable UI patterns.
• Translate complex AI-driven scientific workflows into clear, intuitive, and well-signposted user experiences.
• Work closely with product and research teams to anticipate user needs and features.
• Develop and maintain a modular design system.
• Profile and optimize rendering performance, asset loading, and interaction responsiveness across browsers and devices.
• Integrate real-time data visualizations and dynamic interfaces to empower scientists on our platform.
• Conduct code reviews, enforce engineering best practices, and contribute to front-end architecture decisions.

Qualifications

• 4+ years of professional experience in front-end engineering, with a track record of shipping performant, complex, and data visualization-heavy web applications.
• Proficiency with React (preferred) or a comparable framework, along with deep experience in JavaScript/TypeScript.
• Strong understanding of browser rendering pipelines, performance profiling, and optimization techniques.
• Experience with real-time data handling (e.g., WebSockets, GraphQL subscriptions) and interactive visualizations (e.g., D3.js, Deck.gl, Three.js).
• Ability to transform technical and scientific requirements into elegant, usable visualizations & interfaces.
• Experience building design systems and reusable component libraries.
• Knowledge of accessibility standards and responsive design principles.

Bonus points for:

• Experience with scientific data visualization, computational biology, or AI/ML tools.
• Familiarity with back-end integration patterns for high-throughput data pipelines.

Salary

$175,000 - $240,000  •  Offers equity

Why join us?

• Competitive salary and equity
• Full healthcare coverage — we pay 100% of premiums for you and your dependents
• Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot
• 401(k) company matching
• $300 health and wellness benefit
• Lunch is on us every day you're in the office, and dinner is on us when you're working late
• Regular team offsites and company events
• A fast-moving, mission-driven culture where smart people do their best work and actually enjoy doing it