Jobs in Ajax, Kanada

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

• 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

• 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)

• 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.

• 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.

• 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.

• Lead Core Application Team: Oversee tech vision, architecture, and development.
• App Store for Instrument Connectors: Expose our instrument integrations in a user-friendly marketplace.

• 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.

• 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.

• You dislike fast-paced startup environments.
• You prefer strictly defined roles.

• 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.

• 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

• Experience with scientific or biotech workflows.
• Knowledge of advanced ETL, data streaming, or prompt engineering.

• 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.