Software Architect - Intelligent Document Processing & Agentic Systems
New
M
MachinifyHealthcare Intelligence
Remote - USFull-TimeStaff
Salary230000 - 280000 USD per year
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Job Details
- Experience
- 10+ years
- Required Skills
- PythonJavaScalaLLMDistributed Systems
Requirements
- 10+ years of software engineering experience with a proven track record of owning system architecture at scale
- Experience with Python & Scala/Java — deep experience designing Python-based frameworks and writing idiomatic, well-structured APIs in Python and Scala/Java.
- Demonstrated ability to design effective abstractions: knowing when to generalize, when to keep things concrete, and where to draw boundaries in complex systems
- Experience architecting agentic or multi-step reasoning systems that integrate LLMs into production workflows — framework-agnostic design thinking is valued over familiarity with any specific tool
- Strong background in designing large-scale systems that process unstructured data such as documents, medical records, and images
- Deep understanding of API design principles and building platforms that other engineers build upon
- Proven ability to productionize AI/ML systems with a focus on reliability, observability, and maintainability
- Strong experience with designing with system performance and scaling trade-offs in mind
- Strong CS fundamentals — data structures, distributed systems, asynchronous programming
- Bachelor's or Master's degree in Computer Science, or equivalent experience
Responsibilities
- Own the architecture of Machinify's intelligent document processing platform and agentic evaluation framework — from API design to implementation
- Design abstractions and interfaces that enable agentic workflows to reason over medical records, claims data, and unstructured healthcare documents
- Define the boundaries between orchestration, retrieval, LLM interaction, and domain logic — creating a framework that is principled yet pragmatic. Ensure the system scales.
- Write performant production code — this is a hands-on role where you lead through implementation, not solely through design documents.
- Make foundational technology decisions around prompt architecture, multi-modal LLM integration, RAG patterns, and workflow orchestration
- Drive reliability and observability into AI systems that must operate at healthcare-grade standards
- Collaborate closely with Data Science, Data Engineering, and Product teams to translate complex domain requirements into clean system design
- Reduce technical debt and establish architectural patterns that scale with the platform
- Mentor engineers on system design, API design, and building production-grade AI systems
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