Backend Engineer, Applied AI

Hypha is an AI-native platform transforming asset management across the full lifecycle—acquisition, management, and exit. Focused on healthcare facilities and multifamily real estate, we're revolutionizing the industry through three key pillars:

• Observability: Providing real-time visibility into asset performance, deal progress, and market conditions for all stakeholders

• Intelligence: Enabling AI-driven multidimensional optimization with risk scores, tax strategies, and benchmarking

• Orchestration: Creating seamless workflows and a single source of truth to eliminate inefficiencies

As a Backend Engineer, Applied AI at Hypha, you’ll build and improve the AI systems that power the core of the platform. This includes designing and operating document processing pipelines, building extraction agents, developing entity resolution and computed attribute systems, and shaping the conversational query interface that allows users to interact with complex data.

You’ll work hands-on with LLMs and agent frameworks to design multi-step workflows that transform unstructured information into structured, actionable insights. A large part of the role is building the infrastructure that makes these AI systems reliable, observable, and performant as they operate at scale.

We’re hiring across multiple experience levels for this role, from engineers early in their careers to more senior engineers with deeper systems and architecture experience. Level and compensation will be determined through the interview process.

• Design and build AI agent workflows — document extraction, entity resolution, and data structuring

• Build reliable backend infrastructure — queues, pipelines, and orchestration using Inngest and Supabase

• Work with PostgreSQL at depth — schema design, query optimization, and data modeling for complex financial data

• Instrument, monitor, and debug AI pipelines — understanding failure modes and building guardrails

• Develop and optimize prompt chains, tool-use patterns, and retrieval strategies

• Collaborate with product and frontend engineers to expose AI capabilities through the product

   

• Strong backend fundamentals — You're experienced with Node.js/TypeScript, PostgreSQL, and building reliable server-side systems. You understand concurrency, queuing, and data pipeline design.

• Applied AI experience — You've built products with LLMs; whether that's agent architectures, RAG systems, extraction pipelines, or tool-use patterns. You understand the practical challenges of working with non-deterministic systems.

• Systems thinking — You can reason about how components interact at scale. You think about failure modes, retries, observability, and cost when designing AI workflows.

• Pragmatic engineering — You ship working systems, not research prototypes. You know when to optimize and when good enough is good enough.

• AI-fluent — You use AI coding tools daily and know how to wield them effectively as a multiplier on top of strong fundamentals.

   

• Experience with workflow orchestration tools (Inngest, Temporal, Step Functions)

• Experience with OCR, document processing, or financial data extraction

• Familiarity with OpenAI and Anthropic APIs, function calling, and structured outputs

• Early-stage startup experience

• Bachelor’s degree minimum

• Be at the cutting edge of applied AI

• Have a large scope and massive impact on the company

• Work directly with the leadership team

• Strong career growth opportunities as we scale

• Competitive compensation package: $180-$225k base salary and equity

If you're ready to help build the future of asset management and are excited by the challenge of bringing AI-driven solutions to complex financial workflows, we want to hear from you.