Principal Engineer - AI & Full Stack

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.

A meeting lands on your calendar

If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.