Principal Engineer - AI & Full Stack

Scispot


Date: 8 hours ago
City: Ontario, CA
Contract type: Full time
Remote
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

  • 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.
  • Elevate Our AI Stack
    • Enhance recommendation engines with prompt engineering and LLMs. Building AI pipelines with LLMs.
    • Introduce NLP for seamless instrument integration.
  • Drive Quality and Automation
    • Implement automated tests.
    • Oversee telemetry improvements.
  • 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.

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