• Design, build, and deploy AI solutions hands-on using Azure AI, Azure OpenAI, and Microsoft Fabric, taking use cases from prototype to production • Own the end-to-end architecture of the Microsoft AI ecosystem, including M365 Copilot, Agent 365, and Power Platform • Develop and manage the enterprise data and analytics platform (Microsoft Fabric) to support AI, RAG, and BI use cases • Build and integrate edge-to-cloud data pipelines for OT and MES signals (e.g. Ignition, AVEVA PI) using Azure IoT and Fabric • Drive AI innovation across customer and commercial processes via Microsoft Dynamics, aligned with broader enterprise architecture • Embed security, identity (Entra ID), privacy, and responsible AI controls into all solutions • Lead and mentor a team of engineers and data scientists, reviewing designs and ensuring delivery excellence • Manage MLOps, technical debt, and lifecycle to ensure scalable, maintainable, and cost-efficient AI solutions

• End-to-end product development • Write clean, reusable, and maintainable code • Write tests to validate the correctness of your code thoroughly • Actively contribute to the identification of the problems and their solutions • Collaborate in a cross-functional team to ensure the project meets business objectives and compliance standards

• Developing and maintaining customer-facing features and components across Content Management, Advertising and Customer Relations • Driving pivotal projects from development to production launch, including landing pages enhancements and expansion of marketing campaign features • Implementation and maintenance of new and existing Product features • Conducting thorough automated unit and integration tests to maintain high-quality standards • Leading technical solution planning and ensuring project goals are met within expected timelines • Engaging and collaborating with stakeholders and other engineering teams on business-critical projects and features

Role Description As a Backend Engineer, you will design and build the services, APIs, data models, and infrastructure that power the company’s product. You will work primarily in Python and PostgreSQL while collaborating closely with product engineers, AI engineers, customers, and company leadership. This is not a narrow API-development role; you will work on production architecture, data systems, model integrations, security, reliability, and product capabilities. What you’ll do - Design, build, and maintain production backend services using Python - Develop APIs that support customer-facing applications and AI workflows - Design scalable relational data models using PostgreSQL - Build integrations with model providers, customer systems, and third-party platforms - Develop systems for asynchronous jobs, event processing, and long-running AI workflows - Deploy and operate services using AWS - Debug production issues across application, data, model, and infrastructure layers - Help shape backend architecture and engineering practices as the company grows Qualifications - Approximately 2–9 years of professional software engineering experience - Strong professional experience with Python - Experience designing and operating production APIs or backend services - Strong understanding of relational databases, SQL, and data modeling - Experience with PostgreSQL or a comparable production database - Familiarity with AWS, GCP, or another major cloud platform - Understanding of application security, authentication, and authorization - Experience debugging and operating systems in production - Ability to independently own technical projects from design through deployment - Comfort making pragmatic engineering decisions in an early-stage environment - Strong communication and cross-functional collaboration skills Nice to have (not required) - Experience building AI, LLM, agent, or machine-learning infrastructure - Experience integrating OpenAI, Anthropic, or other model providers - Familiarity with LLM evaluation, retrieval, embeddings, or vector databases - Experience with Docker, Kubernetes, Terraform, or CI/CD systems - Experience with Redis, Kafka, queues, or event-driven architectures - Experience building multi-tenant SaaS products - Previous experience at an early-stage startup - Experience with data-intensive or distributed systems