- Location
- Cambridge, MA
- Type
- Full-time
- Department
- Engineering
- Education
- PhD
- Source
- RecruiterFlow
Description
- End-to-End Platform Ownership: Design, build, and scale the web platform that enables deal teams to explore, upload, and analyze drug assets from discovery through due diligence and valuation.
- Front-End Architecture & UX: Develop intuitive, data-rich interfaces using modern frameworks (React/Next.js preferred) that empower users to manage deal pipelines, upload documents, and interpret LLM-driven insights.
- Workflow & Orchestration: Implement robust backend services and job orchestration layers (e.g., FastAPI, Node, or similar) that coordinate document ingestion, model execution, and results delivery across the platform.
- Data Visualization & Insight Delivery: Create dynamic, interactive components that visualize scientific assessments, risk analyses and deal insights generated by ML pipelines.
- API & Integration Engineering: Design and maintain clean, scalable APIs between the core LLM orchestration layer and the platform. Collaborate closely with ML engineers to expose model outputs as user-ready insights.
- Reliability & Scalability: Deploy and monitor platform services on AWS (or equivalent). Ensure high availability, low latency, and secure handling of sensitive scientific and deal data.
- Collaboration & Product Thinking: Work cross-functionally with ML engineers, product leads, and domain experts to translate scientific and business logic into actionable workflows that drive decision-making.
- Continuous Improvement: Champion engineering best practices — automated testing, CI/CD, observability, and modular architecture — while staying current on advances in AI-driven platform development.
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Education: Bachelor’s, Master’s, or Ph.D. in Computer Science, Software Engineering, or a related technical field.
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Full-Stack Engineering: Proven experience building modern web applications end-to-end — from intuitive, performant front-ends (React, Next.js, or similar) to robust, scalable back-ends (FastAPI, Node.js, or equivalent).
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Product & Platform Development: Hands-on experience designing and implementing complex, data-driven applications that integrate with APIs, asynchronous job systems, or machine learning backends.
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Frontend Architecture & UX: Strong command of component-based design, state management, and visualization frameworks (e.g., React Query, Redux, D3, Plotly) to deliver interactive, insight-driven user experiences.
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Backend & API Engineering: Expertise in developing RESTful or GraphQL APIs, integrating authentication/authorization, and managing event-driven workflows and background jobs.
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Database & Data Flow: Comfort working with both relational and NoSQL databases (e.g., Postgres, MongoDB, DynamoDB), and designing efficient data access layers for large, dynamic datasets.
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Cloud Infrastructure & DevOps: Experience deploying full-stack applications in cloud environments (AWS, GCP, or Azure) using modern DevOps practices — including Docker, Kubernetes, Terraform, and CI/CD pipelines.
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Security & Compliance Awareness: Familiarity with best practices for secure data handling, user authentication, and compliance (especially valuable in healthcare, life sciences, or enterprise environments).
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Collaboration & Product Mindset: Strong communication and collaboration skills; ability to work closely with ML engineers, product managers, and scientific domain experts to deliver elegant, high-impact user workflows.