Satori Analytics

Frontend Engineer

• Ship product features: Build chat interfaces, admin dashboards, authentication flows, and document workflows that enterprise users rely on every day.
• Own the full lifecycle: Contribute across the full frontend stack, from discussing requirements with product, to writing typed components, to shipping and monitoring in production.
• Translate AI into UI: Turn LLM capabilities (streaming responses, citations, voice input, multi-agent flows) into intuitive, trustworthy interfaces.
• Set the quality bar: Shape frontend conventions the team follows: accessibility, performance, testing patterns, and component design.
• Keep systems healthy: Monitor and troubleshoot production with Azure Application Insights and structured Winston logs to ensure reliability and great UX.
• Collaborate across the stack: Work closely with Python backend engineers, product stakeholders, and designers to turn use cases into working features.
• Document and share: Maintain clear component documentation and architectural notes to keep the team aligned as the products grow.
• Agile team structure: Participate in agile methodology ceremonies and catch up with your team regularly.

Front-End Engineer

Machine Learning Engineer

• **What Your Day Might Look Like:**
• - **Make AI production-ready:** Design and maintain the infrastructure that takes ML models from experimentation to reliable, scalable deployment.
• - **Build automated ML pipelines:** Create repeatable workflows for training, evaluation, deployment, and retraining — with versioning and reproducibility built in.
• - **Deploy and serve models:** Package models as production services across cloud, on-premise, or hybrid environments, with performance and reliability in mind.
• - **Monitor what matters:** Track model performance, data drift, system health, and production signals to support better retraining and troubleshooting decisions.
• - **Enable AI teams:** Work closely with Data Scientists, AI Engineers, and Software Engineers to improve how models are tested, deployed, and maintained.
• - **Set the standard:** Contribute to best practices around CI/CD, model registry, observability, security, and governance.
• - **Support GenAI at scale:** Help deploy and optimize LLM-based systems, including inference services, GPU usage, and RAG infrastructure where needed.
• - **Keep systems secure and reliable:** Ensure ML deployments follow strong practices around access control, data governance, and operational resilience.

Senior MLOps Engineer

Backend Engineer

• Build reliable software: Design and develop Python applications, APIs, and microservices that are clean, tested, and built to scale.
• Create strong foundations: Build and maintain data ingestion and processing pipelines that are reliable, observable, and easy to support.
• Work across teams: Collaborate with Data Scientists, Data Engineers, AI Engineers, and domain experts to turn analytical needs into solid software solutions.
• Ship with quality: Use Git, CI/CD, code reviews, testing, and documentation to keep delivery fast and maintainable.
• Solve real problems: Break down business needs into practical technical solutions, balancing speed, quality, and long-term scalability.
• Keep improving: Contribute to engineering best practices and help raise the quality of how we build software at Satori.

Python Developer

• **What Your Day Might Look Like:**
• - **Ship product features:** Build chat interfaces, admin dashboards, authentication flows, and document workflows that enterprise users rely on every day.
• - **Own the full lifecycle:** Contribute across the full frontend stack, from discussing requirements with product, to writing typed components, to shipping and monitoring in production.
• - **Translate AI into UI:** Turn LLM capabilities (streaming responses, citations, voice input, multi-agent flows) into intuitive, trustworthy interfaces.
• - **Set the quality bar:** Shape frontend conventions the team follows: accessibility, performance, testing patterns, and component design.
• - **Keep systems healthy:** Monitor and troubleshoot production with Azure Application Insights and structured Winston logs to ensure reliability and great UX.
• - **Collaborate across the stack:** Work closely with Python backend engineers, product stakeholders, and designers to turn use cases into working features.
• - **Document and share:** Maintain clear component documentation and architectural notes to keep the team aligned as the products grow.
• - **Agile team structure:** Participate in agile methodology ceremonies and catch up with your team regularly.

Frontend Developer

AI Engineer

• **What Your Day Might Look Like:**
• - **Build AI magic:** Design and develop AI workflows and/or models in Python, with a focus on leveraging LLMs. You will learn how to bridge AI/ML and the Software Engineering world, building scalable AI solutions.
• - **Team collaboration:** Work closely with data scientists, developers, and domain experts to brainstorm ideas, share updates, and guide progress.
• - **Stay ahead:** Research new trends and integrate cutting-edge techniques into your projects.
• - **Problem-solving:** Translate business needs into practical ML/AI solutions, while communicating results clearly.
• - **Document everything:** Ensure your work is reproducible and easily understood across the team.