Senior/Principal Full-stack Engineer

Location: REMOTE / Kitchener-Waterloo, Ontario. This job allows you to work remotely.

Role Overview

- You will own their AI and full-stack engineering efforts

- You will shape next generation features that help scientists run experiments faster

- You will guide the 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 the 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.

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.

Special Perks

Why join them?

- 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.

Must Have Skills

- Proficiency in Java, Python, React & JavaScript

- 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.

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

Nice to Have Skills

- Experience with scientific or biotech workflows.

- Knowledge of advanced ETL, data streaming, or 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.

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