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 AIand 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 loops10% collaboration, planning, and roadmap refinement10% data engineering, infrastructure and embedding strategies10% LLM experimentation (prompting, AIpipelines, graph DBs, vector DBs)What You’ll Do
Architect and ScaleBuild robust backend services with intuitive UI / UX (React, Java Spring Boot, AWS, Kubernetes).
Develop new AI-based features for enterprise customers.Elevate Our AI StackEnhance recommendation engines with prompt engineering and LLMs. Building AIpipelines with LLMs.
Introduce NLP for seamless instrument integration.Drive Quality and AutomationImplement automated tests.
Oversee telemetry improvements.Lead and MentorCollaborate with product, data, and design teams.
Grow a team of engineers focused on cutting-edge AI tools.Required Skills
Proficiency in Java, Python, React &JavacriptExperience 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 AIUse prompt engineering and AIpipelines with LLMs for better suggestions.
Aim for performance and scalability.Scale API and GLUE LayerBuild strong ETL support for enterprise loads.
Build SDK framework for Scispot APIsIntroduce NLP for Instrument IntegrationOffer script templates so scientists can process data easily.
Suggest Telemetry ImprovementsImprove monitoring for infrastructure health.
Graphical Chain of CustodyLet users query sample journeys with prompts using graph database
Month 7-12, you will :
EKS MigrationGrow &Maintain AWSEKScluster
Automated TestingIncrease backend unit test coverage.
MCP Layer for RecommendationAllow AI agents to take simple actions for scientists.
Upgrade SearchImprove OpenSearch and vector databases.
Memory Layer for AgentsReduce reliance on retrieval-augmented generation by building memory layer for AIagents
Month 13-24, you will :
Lead Core Application TeamOversee tech vision, architecture, and development.
App Store for Instrument ConnectorsExpose our instrument integrations in a user-friendly marketplace.
Tech Stack :
Frontend : React JS and TypescriptBackend : Elastic Search, AWS Lambda, Rabbit MQ, Mongo DB, S3, Java Spring BootArchitecture : Microservices integrated with GraphQL and Rest APIsAI Infrastructure : TensorFlow (Proprietary ML) , Azure AI Service, Azure Open AI service, AIPipelines, Programmatic Prompt EngineeringIdeal 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 AIarchitectures.Good understanding of learning how to build AIpipelines 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.#J-18808-Ljbffr