Senior Full-stack Engineer - AI

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

Our client is one of Canada's fastest-growing startups, drawing the blueprint for the future of biotech data. Their mission is to develop cutting-edge data infrastructure for biotech labs globally. By blending technology with biotechnology, they are making every lab an AI Powerhouse. You'll have a chance to make a real impact, craft the digital spine of global biotech labs, and benefit from generous stock options.

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?

1. 50% coding and system design (React, Python, Java + AI integration)
2. 20% product iteration and user feedback loops
3. 10% collaboration, planning, and roadmap refinement
4. 10% data engineering, infrastructure and embedding strategies
5. 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.
• Enhance recommendation engines with prompt engineering and LLMs.
• Introduce NLP for seamless instrument integration.
• Implement automated tests and oversee telemetry improvements.
• 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 using prompt engineering and AI pipelines with LLMs for better suggestions.
• Scale API and GLUE Layer.
• Build strong ETL support for enterprise loads.
• Introduce NLP for Instrument Integration.
• Improve monitoring for infrastructure health.
• Let users query sample journeys with prompts using graph database.

Month 7-12, you will:

• Grow & Maintain AWS EKS cluster.
• Increase backend unit test coverage.
• Allow AI agents to take simple actions for scientists.
• Improve OpenSearch and vector databases.
• Reduce reliance on retrieval-augmented generation by building memory layer for AI agents.

Month 13-24, you will:

• Oversee tech vision, architecture, and development.
• Expose 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.