Job Description
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 tot his job