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Sr. Fullstack Engineer

DRH Search

  • Cambridge, Massachusetts
  • 2 days ago

    Highlights

    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. 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.

    Numbers & Facts

    LocationCambridge, Massachusetts
    Websitehttps://drhsearch.com/

    Description

     We've partnered with a well-funded, fast-growing startup in the biotech space to help them find Sr. Fullstack Engineers. Their product helps pharma, biotech, and investors figure out whether a drug or biotech asset is worth acquiring, licensing, investing in, or developing. They're headquartered in Cambridge, MA and looking for candidates who can come into the office twice a week, while working remotely three days a week.
     
    What you'll do:
    • 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.
    What you'll bring:

    • Education: Bachelor’s, Master’s, or Ph.D. in Computer Science, Software Engineering, or a related technical field.

    • 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).

    • Product & Platform Development: Hands-on experience designing and implementing complex, data-driven applications that integrate with APIs, asynchronous job systems, or machine learning backends.

    • 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.

    • Backend & API Engineering: Expertise in developing RESTful or GraphQL APIs, integrating authentication/authorization, and managing event-driven workflows and background jobs.

    • 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.

    • 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.

    • Security & Compliance Awareness: Familiarity with best practices for secure data handling, user authentication, and compliance (especially valuable in healthcare, life sciences, or enterprise environments).

    • 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.

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