Principal Engineer - AI & Full Stack

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** 1. 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. 2. Elevate Our AI Stack * Enhance recommendation engines with prompt engineering and LLMs. Building AI pipelines with LLMs. * Introduce NLP for seamless instrument integration. 3. Drive Quality and Automation * Implement automated tests. * Oversee telemetry improvements. 4. 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.

Scispot is a fully configurable workflow automation platform for fast-growing life science companies. Our customers use Scispot to design and automate their workflows at all stages of their R&D, from planning, lab execution to reporting collaboratively.