Back-End Engineer

As a Back-End Engineer at HelloBiome, you will play a critical role in building and optimizing the infrastructure that powers one of our AI solutions based on large language models (LLMs). You will work closely with researchers, and software teams to design, implement, and maintain scalable back-end systems that enable rapid experimentation and high-quality outputs. Your work will ensure our platforms are robust, secure, and ready for production at scale, directly supporting the advancement of our microbiome-based solutions. You will work in a collaborative environment, translating prototypes into reliable back-end services, and continuously improving our technology stack to meet evolving business and research needs. Your experimental and research-oriented mindset will be key as you partner with scientists to iterate quickly, validate new ideas, and deliver back-end solutions that set the standard for quality and innovation in the microbiome field. This role includes a competitive cash salary and equity package. Compensation is calculated based on the location of the team member, reflecting HelloBiome’s commitment to fair and equitable remuneration. Qualifications Experimental and research-oriented mindset, comfortable working in fast-paced, iterative environments to rapidly test, evaluate, and refine back-end systems for quality outputs. Excellent problem-solving skills, attention to detail, and a passion for delivering reliable, maintainable code. 5+ years of experience in back-end software engineering, with a focus on building scalable, high-performance systems. Proven expertise in designing and implementing APIs, microservices, and distributed systems using modern backend frameworks (e.g., Python/FastAPI, Node.js/Express, Go, or similar). Deep understanding of cloud infrastructure (AWS, Azure, or Google Cloud), containerization (Docker, Kubernetes), and CI/CD pipelines for robust deployment of data-intensive services. Strong knowledge of database systems (SQL and NoSQL), data modeling, and data pipeline development for handling large-scale, unstructured data. Strong communication skills to work effectively with cross-functional teams and contribute to technical discussions and architectural decisions. Experience integrating and optimizing large language models (LLMs) or other AI/ML models into production environments, including model serving, monitoring, and versioning is a plus. Work with Vector Stores (Vector Databases) to enable efficient storage, retrieval, and management of embeddings and other high-dimensional data for AI applications is a plus. Responsibilities Design, build, and maintain scalable back-end infrastructure to support AI solutions, ensuring high availability and performance. Collaborate with researchers and data scientists to translate experimental models and prototypes into robust, production-ready back-end. Develop and optimize APIs, microservices, and data pipelines for efficient integration and deployment of LLMs and other AI models. Implement monitoring, logging, and versioning systems to ensure reliability, traceability, and continuous improvement of AI services. Ensure back-end systems adhere to security, privacy, and compliance standards, especially when handling sensitive health data. Foster a culture of experimentation and innovation, rapidly iterating on back-end solutions to support research and deliver high-quality outputs. Contribute to architectural decisions, code reviews, and best practices to maintain a high standard of code quality. #J-18808-Ljbffr