Senior Backend Data Engineer
at Eleos Health · 101-250 employees
Series C · $60M · Jan 2025
- Seniority
- Senior
- Location
- Tel Aviv District, Israel
- Posted
- 5d ago
pythonfastapikafkaawskuberneteslambdasparkairflowdbtllm
at Eleos Health · 101-250 employees
Eleos Health builds behavioral-health AI that automates clinical documentation, analyzes therapy sessions using speech-to-insights and specialized LLMs, surfaces clinical and compliance insights, and integrates with provider workflows and EHRs.
<div class="content-intro"><p><strong>Who is Eleos Health?</strong></p> <p>Today, more people than ever are speaking publicly about their mental health. Whether it's ourselves, our friends and family or even public figures, taking care of your behavioral health is no longer a taboo, it's vital, and it's only human. <br><br>Eleos is on a mission to help deliver the world's most effective behavioral care through data, measurement, and personalization. Or simply put, <strong>we want to give clinicians the support they need to do the important work only they can do</strong>.</p></div><div class="p-rich_text_section"><strong>What is this opportunity?</strong><br>We are seeking a <strong data-stringify-type="bold">Senior Backend Engineer – Data Platform</strong> to join our expanding team and play a crucial role in designing, building, and maintaining robust and scalable data pipelines and infrastructure. In this role, you will directly enable data-driven decision-making and support the development and deployment of AI/ML products that power Eleos Health.<br><br>You’ll collaborate closely with engineering, product, and data science teams to ensure our data systems are high-quality, resilient, and scalable as we grow. As a Senior Backend Engineer on our Data Platform team, you will drive efforts to deliver reliable, efficient, and consistent data services across the organization. You will also help enable the rapid development and deployment of advanced features, insights, and AI-driven capabilities that improve outcomes for clinicians and clients.<br><br><strong>Who are you?</strong><br>You are a seasoned backend or data engineer with experience working on production-grade ML/AI-powered products. You thrive in fast-paced, high-ownership environments and are passionate about building scalable and reliable systems. You understand the unique requirements of delivering AI/ML features in production, and you are comfortable working with modern technologies in the LLM/RAG ecosystem.<br>You pride yourself on delivering high-quality solutions quickly, without sacrificing design or reliability. You’re known for your responsiveness, collaborative spirit, and service-oriented mindset—especially when you’re on-call and the stakes are high.How will you contribute?</div> <ul class="p-rich_text_list p-rich_text_list__bullet p-rich_text_list--nested" data-stringify-type="unordered-list" data-list-tree="true" data-indent="0" data-border="0"> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Design, implement, and maintain</strong> scalable and reliable data pipelines and backend systems supporting both operational and analytical needs, with a focus on ML/AI product enablement.</li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Ensure data processing is optimized for speed, efficiency, and fault tolerance, enabling seamless integration with AI/ML workflows and reliable performance across all Eleos Health products.</strong></li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Monitor and improve</strong> uptime, reliability, and observability of our data infrastructure and pipelines.</li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Build and maintain systems</strong> to ensure data quality, consistency, and usability across the organization, enabling advanced analytics and AI solutions.</li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Work closely with product and engineering teams</strong> to deliver new features rapidly and with a high standard of technical excellence.</li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Drive innovation</strong> in how we build, measure, and optimize data features, backend services, and AI product integrations.</li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Participate in on-call rotations</strong> with a service-oriented approach and fast responsiveness.</li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Lead scalability efforts</strong> to support increasing data volumes, expanding AI/ML initiatives, and new product launches.</li> </ul> <div class="p-rich_text_section"><strong>What qualifications and skills will help you to be successful?</strong></div> <ul class="p-rich_text_list p-rich_text_list__bullet p-rich_text_list--nested" data-stringify-type="unordered-list" data-list-tree="true" data-indent="0" data-border="0"> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">At least 5 years of experience</strong> with Python in backend or data engineering roles, designing and operating large-scale data pipelines, backend services, and data infrastructure in production environments.</li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Hands-on experience working on ML/AI-powered products in production</strong>, with strong understanding of requirements for integrating data platforms with AI features.</li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Familiarity with modern LLM (Large Language Model) and RAG (Retrieval-Augmented Generation) technologies</strong>, and experience supporting their deployment or integration.</li> <li data-stringify-indent="0" data-stringify-border="0"><strong data-stringify-type="bold">Familiar with or have worked with these technologies (or alternatives):</strong> <ul class="p-rich_text_list p-rich_text_list__bullet p-rich_text_list--nested" data-stringify-type="unordered-list" data-list-tree="true" data-indent="1" data-border="0"> <li data-stringify-indent="1" data-stringify-border="0"><strong data-stringify-type="bold"