Note: The job is a remote job and is open to candidates in USA. People In AI is a scaling, venture-backed lending technology business that is building the next generation of AI-enabled operational infrastructure. The Azure AI Engineer role focuses on architecting and building durable AI workflow infrastructure on Microsoft Azure, connecting various systems to improve lending operations.
Responsibilities
- Build the AI platform and workflow orchestration layer for lending operations across underwriting, fulfillment, document processing, borrower engagement, and eligibility workflows
- Design durable, event-driven automation systems using Azure services, workflow engines, APIs, messaging, retries, checkpointing, recovery, and asynchronous coordination
- Move early AI and automation proofs of concept into production-grade systems with proper reliability, observability, auditability, and human-in-the-loop controls
- Develop AI-enabled workflows using LLM APIs, agentic automation, RAG, tool orchestration, document extraction, classification, routing, and operational decision support
- Partner with software engineering, AI/data, DevOps, product, and lending operations teams to build frameworks that can scale beyond the first use cases
- Support the data lakehouse foundations that will underpin future automation, analytics, machine learning, and optimization workflows
- Help define the standards, architecture, and future team capability for AI automation in a regulated operational environment
Skills
- Strong experience architecting and shipping production software, platform engineering, distributed systems, workflow automation, or AI infrastructure
- Hands-on Azure engineering experience, ideally across cloud-native infrastructure, event-driven systems, containerized services, APIs, and secure platform patterns
- Experience with workflow orchestration tools such as Temporal, Camunda, Azure Durable Functions, or similar platforms
- Ability to build and reason about AI-enabled workflows involving LLMs, agents, RAG, document intelligence, tool orchestration, and human-in-the-loop systems
- Strong software engineering ability in one or more of Python, TypeScript, Go, C#, or .NET, with comfort working across modern APIs and microservices
- Practical understanding of observability, traceability, governance, PII handling, auditability, and production reliability
- Clear ownership mindset, strong communication, curiosity, and the ability to explain what you shipped, what broke, how you fixed it, and what impact it created
- Proven experience building production systems, not just experimenting with AI tools or listing frameworks on a resume
- Strong Azure platform engineering experience
- Workflow orchestration, distributed systems, event-driven architecture, or durable execution experience
- U.S. work authorization without visa sponsorship; U.S. citizens or green card holders only
- Ability to work primarily with East Coast stakeholders
Company Overview