Senior Software Engineer (Full Stack)
PRUDENTIA SCIENCES, INC.
Cambridge, MA, United States
about 1 month ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$153,000.0 - $235,000.0
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Artificial Intelligence
Amazon Web Services
Business Logic
Automation of Tests
Microsoft Azure
Cloud Computing
Databases
Continuous Integration
Data Security
Database Applications
DevOps
+27 more
Amazon DynamoDB
PostgreSQL
Machine Learning
MongoDB
Node.Js
NoSQL
Rapid Prototyping Process
Next.js
Software Engineering
Data Streaming
Systems Integration
Web Applications
Cloud Platform System
ReactJS
System Availability
Large Language Models
Backend
Fastapi
Kubernetes
Information Technology
Low Latency
Plotly
Front End Software Development
React Redux
Restful APIs
Terraform
Docker
Job 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.
Requirements
- 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.
Soft Skills:
- Strong problem-solving skills and an analytical mindset.
- Passion for continuous learning, rapid prototyping, and iterating based on user needs.
- Autonomous, self-starter attitude with a strong sense of ownership.
- Excellent communication skills-able to explain technical ideas clearly to non-technical audiences.
- Collaborative team player with a desire to build things that truly matter.
Bonus
- Experience in healthcare, life sciences, or biopharma sectors is nice, but not required. More important is a willingness to dive into the field and a curiosity to learn about life sciences and the drug development process, and how deal making revolves around it.
Benefits & conditions
We are open to exceptional talent that is fully remote in the U.S. but have strong preference towards someone who can come in our Boston, San Francisco, or New York City office twice per week (Tues/Thurs).
Compensation Range: $153K - $235K
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