Principal Engineer - AI & Full Stack

Job Description

<p><h3>Overview</h3><p>Scispot is building the digital backbone for scientific discovery. We empower biotech teams by unifying lab operations, data flow, and AI-driven insights.</p><h3>Role Overview</h3><ul><li>You will own our AI and full-stack engineering efforts</li><li>You will shape next generation features that help scientists run experiments faster</li><li>You will guide our platform's scalability and drive new integrations for lab instruments</li></ul><h3>How will you spend your time?</h3><ul><li>50% coding and system design (React, Python, Java + AI integration)</li><li>20% product iteration and user feedback loops</li><li>10% collaboration, planning, and roadmap refinement</li><li>10% data engineering, infrastructure and embedding strategies</li><li>10% LLM experimentation (prompting, AI pipelines, graph DBs, vector DBs)</li></ul><h3>What You’ll Do</h3><ul><li><b>Architect and Scale</b><p>Build robust backend services with intuitive UI / UX (React, Java Spring Boot, AWS, Kubernetes).</p></li><li><b>Develop new AI-based features for enterprise customers.</b></li><li><b>Elevate Our AI Stack</b><p>Enhance recommendation engines with prompt engineering and LLMs. Build AI pipelines with LLMs.</p></li><li><b>Introduce NLP for seamless instrument integration.</b></li><li><b>Drive Quality and Automation</b><p>Implement automated tests.</p></li><li><b>Oversee telemetry improvements.</b></li><li><b>Lead and Mentor</b><p>Collaborate with product, data, and design teams.</p></li><li>Grow a team of engineers focused on cutting-edge AI tools.</li></ul><h3>Required Skills</h3><ul><li>Proficiency in Java, Python, React & JavaScript</li><li>Experience deploying to AWS (EKS, Lambda, or EC2).</li><li>Deep knowledge of AI pipelines, LLMs, and NLP libraries.</li><li>Familiarity with data stores (OpenSearch, vector databases, graph databases).</li><li>Strong leadership and communication skills.</li></ul><h3>Bonus Skills</h3><ul><li>Experience with scientific or biotech workflows.</li><li>Knowledge of advanced ETL, data streaming, or prompt engineering.</li></ul><h3>Your Two Year Roadmap</h3><h3>Month 1-6, you will :</h3><ul><li>Enhance Recommendation AI</li><li>Use prompt engineering and AI pipelines with LLMs for better suggestions.</li><li>Aim for performance and scalability.</li><li>Scale API and GLUE Layer</li><li><b>Build strong ETL support for enterprise loads.</b></li><li>Build SDK framework for Scispot APIs</li><li>Introduce NLP for Instrument Integration</li><li>Offer script templates so scientists can process data easily.</li><li>Suggest Telemetry Improvements</li><li><b>Improve monitoring for infrastructure health.</b></li><li>Graphical Chain of Custody</li><li>Let users query sample journeys with prompts using graph database</li></ul><h3>Month 7-12, you will :</h3><ul><li>EKS Migration</li><li><b>Grow & Maintain AWS EKS cluster</b></li><li>Automated Testing</li><li><b>Increase backend unit test coverage.</b></li><li>MCP Layer for Recommendation</li><li><b>Allow AI agents to take simple actions for scientists.</b></li><li>Upgrade Search</li><li><b>Improve OpenSearch and vector databases.</b></li><li>Memory Layer for Agents</li><li><b>Reduce reliance on retrieval-augmented generation by building memory layer for AI agents</b></li></ul><h3>Month 13-24, you will :</h3><ul><li>Lead Core Application Team</li><li><b>Oversee tech vision, architecture, and development.</b></li><li>App Store for Instrument Connectors</li><li>Expose our instrument integrations in a user-friendly marketplace.</li></ul><h3>Tech Stack</h3><ul><li>Frontend : React JS and Typescript</li><li>Backend : Elastic Search, AWS Lambda, Rabbit MQ, Mongo DB, S3, Java Spring Boot</li><li>Architecture : Microservices integrated with GraphQL and Rest APIs</li><li>AI Infrastructure : TensorFlow (Proprietary ML) , Azure AI Service, Azure Open AI service, AIPipelines, Programmatic Prompt Engineering</li></ul><h3>Ideal Candidate Profile</h3><ul><li>Proficient with AWS and its suite of data services.</li><li>Hands-on experience with tools such as Lambda function, MQ, Java Spring Boot, Elastic Search, Python, MongoDB, DynamoDB, and S3 bucket.</li><li>Strong programming skills, particularly in Python, Java, React & JavaScript.</li><li>Good understanding of different Agentic AI architectures.</li><li>Good understanding of learning how to build AI pipelines with LLMs.</li><li>A solid grasp of microservices and associated best practices.</li><li>Experience in data engineering and orchestration is preferred.</li><li>Loves working in a fast paced startup environment.</li></ul><h3>Why Join Scispot?</h3><ul><li>Work from anywhere but ideally based out of Canada.</li><li>Engage in challenging, impactful work in the realm of biotech data and AI.</li><li>Competitive stock options.</li><li>Unlimited growth upside.</li></ul><h3>Why You Might Love This Role</h3><ul><li>You want to shape the future of scientific research.</li><li>You enjoy solving complex AI challenges.</li><li>You like leading from the front, mentoring, and guiding teams.</li><li>A chance to build next-gen AI tools for lab workflows.</li><li>Leadership role with a high level of autonomy.</li></ul><h3>Why You Might Not</h3><ul><li>You dislike fast-paced startup environments.</li><li>You prefer strictly defined roles.</li></ul><p>J-18808-Ljbffr</p></p>
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