Scispot is building the digital backbone for scientific discovery. We empower biotech teams by unifying lab operations, data flow, and AI-driven insights.
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.
Apply Now
Apply Now