Principal Engineer - AI & Full Stack

Scispot is building the digital backbone for scientific discovery. We empower biotech teams by unifying lab operations, data flow, and AI-driven insights.

‍Role Overview

• You will own our AI and full-stack engineering efforts
• You will shape next generation features that help scientists run experiments faster
• You will guide our platform's scalability and drive new integrations for lab instruments

How will you spend your time?

• 50% coding and system design (React, Python, Java + AI integration)
• 20% product iteration and user feedback loops
• 10% collaboration, planning, and roadmap refinement
• 10% data engineering, infrastructure and embedding strategies
• 10% LLM experimentation (prompting, AI pipelines, graph DBs, vector DBs)

What You’ll Do

1. Architect and Scale
   • Build robust backend services with intuitive UI/UX (React, Java Spring Boot, AWS, Kubernetes).
   • Develop new AI-based features for enterprise customers.
2. Elevate Our AI Stack
   • Enhance recommendation engines with prompt engineering and LLMs. Building AI pipelines with LLMs.
   • Introduce NLP for seamless instrument integration.
3. Drive Quality and Automation
   • Implement automated tests.
   • Oversee telemetry improvements.
4. Lead and Mentor
   • Collaborate with product, data, and design teams.
   • Grow a team of engineers focused on cutting-edge AI tools.‍

Required Skills

• Proficiency in Java, Python, React & Javacript
• Experience deploying to AWS (EKS, Lambda, or EC2).
• Deep knowledge of AI pipelines, LLMs, and NLP libraries.
• Familiarity with data stores (OpenSearch, vector databases, graph databases).
• Strong leadership and communication skills.

Bonus Skills

• Experience with scientific or biotech workflows.
• Knowledge of advanced ETL, data streaming, or prompt engineering.

Your Two Year Roadmap

Month 1-6, you will:

• Enhance Recommendation AI
  • Use prompt engineering and AI pipelines with LLMs for better suggestions.
  • Aim for performance and scalability.
• Scale API and GLUE Layer
  • Build strong ETL support for enterprise loads.
  • Build SDK framework for Scispot APIs
• Introduce NLP for Instrument Integration
  • Offer script templates so scientists can process data easily.
• Suggest Telemetry Improvements
  • Improve monitoring for infrastructure health.
• Graphical Chain of Custody
  • Let users query sample journeys with prompts using graph database

Month 7-12, you will:

• EKS Migration
  • Grow & Maintain AWS EKS cluster
• Automated Testing
  • Increase backend unit test coverage.
• MCP Layer for Recommendation
  • Allow AI agents to take simple actions for scientists.
• Upgrade Search
  • Improve OpenSearch and vector databases.
• Memory Layer for Agents
  • Reduce reliance on retrieval-augmented generation by building memory layer for AI agents

Month 13-24, you will:

• Lead Core Application Team
  • Oversee tech vision, architecture, and development.
• App Store for Instrument Connectors
  • Expose our instrument integrations in a user-friendly marketplace.

Tech Stack:

• Frontend: React JS and Typescript
• Backend: Elastic Search, AWS Lambda, Rabbit MQ, Mongo DB, S3, Java Spring Boot
• Architecture: Microservices integrated with GraphQL and Rest APIs
• AI Infrastructure:  TensorFlow (Proprietary ML) ,  Azure AI Service,  Azure Open AI service, AI Pipelines, Programmatic Prompt Engineering

Ideal Candidate Profile:

• Proficient with AWS and its suite of data services.
• Hands-on experience with tools such as Lambda function, MQ, Java spring boot, Elastic Search, Python, Mongo DB, Dynamo DB, and S3 bucket.
• Strong programming skills, particularly in Python, Java, React & Javascript.
• Good understanding of different Agentic AI architectures.
• Good understanding of learning how to build AI pipelines with LLMs.
• A solid grasp of microservices and associated best practices.
• Experience in data engineering and orchestration is preferred.
• Loves working in a fast paced startup environment.

Why Join Scispot?:

• Work from anywhere but ideally based out of Canada.
• Engage in challenging, impactful work in the realm of biotech data and AI.
• Competitive stock options.
• Unlimited growth upside.

Why You Might Love This Role

• You want to shape the future of scientific research.
• You enjoy solving complex AI challenges.
• You like leading from the front, mentoring, and guiding teams.
• A chance to build next-gen AI tools for lab workflows.
• Leadership role with a high level of autonomy.

Why You Might Not

• You dislike fast-paced startup environments.
• You prefer strictly defined roles.

Interview Process

• Initial screening followed by coding interview