Principal Engineer – AI and 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.

We are hiring a Principal Engineer – AI and Full Stack to lead an R&D scientific innovation project aimed at advancing Scispot’s AI-powered Lab Operating System. The role will focus on designing, prototyping, and commercializing new features that integrate AI, data science, and full-stack engineering to improve biotech lab workflows.

Key Activities

• Lead research and development of AI-enabled modules for data capture, analysis, and visualization in life science labs.
• Prototype and test new product features with pilot customers to validate technical feasibility and market fit.
• Conduct technical and market analysis to optimize adoption of AI-driven lab tools.
• Build and refine full-stack architectures that integrate with lab instruments, APIs, and cloud-based platforms.
• Deliver measurable outcomes, such as reducing manual data entry time and increasing workflow automation in pilot labs.

Outcomes & Impact

• Creation of innovative, market-ready tools that enhance lab efficiency and data quality.
• Contribute to commercialization efforts through pilot deployments and adoption in Canadian and international labs.

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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Application If shaping the future of biotech data infrastructure resonates with you, we'd like to hear more. Send your resume to [email protected] .

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