Job description

Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs. JD for Software Architect: Software Architect | Intelligent Document Processing & Agentic Systems Location: Remote - US About Machinify Machinify is a healthcare intelligence platform deployed across 85+ health plans, serving over 270 million lives. We build AI-powered systems for payment integrity and audit solutions that optimize financial outcomes and reduce healthcare costs — processing hundreds of millions of documents and validating millions of claims annually. The Role We are seeking a Software Architect to own the design and implementation of our intelligent document processing and agentic evaluation framework. This is a hands-on, Senior Staff-level technical leadership role responsible for setting the architectural direction for how our platform ingests, understands, and reasons over complex healthcare documents at scale. This role requires both architectural vision and strong implementation skills. You will design the APIs, abstractions, and frameworks that power agentic case analysis — and build them alongside a team of experienced engineers. The ideal candidate brings deep expertise in system design, has strong convictions about where abstraction boundaries belong, and writes Python that sets the standard for the team. What You'll Do 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 What We're Looking For 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 Nice to Have Experience with Spark, Flink, Kafka, Airflow, or Ray Knowledge of Prometheus, Grafana, and observability tooling Background in healthcare, fintech, or other regulated industries Cross-functional collaboration experience with data scientists and ML engineers What We Offer Work from anywhere in the US! Machinify is digital-first. Top Medical/Dental/Vision offerings FSA/HSA Tuition reimbursement Competitive salary, 401(k) with company match Unlimited PTO Additional health and wellness benefits and perks Flexible and trusting environment where you’ll feel empowered to do your best work The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels and the base salary can range from $230k-$280k+ based on your assessed level. Compensation also includes meaningful equity, healthcare, unlimited PTO, and more. Equal Employment Opportunity at Machinify We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: machinify.com

Requirements

Must-haves

Software Architect | Intelligent Document Processing & Agentic Systems
Location: Remote - US
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
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

Nice-to-haves

Experience with Spark, Flink, Kafka, Airflow, or Ray
Knowledge of Prometheus, Grafana, and observability tooling
Background in healthcare, fintech, or other regulated industries
Cross-functional collaboration experience with data scientists and ML engineers

Application prep

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Keywords to mirror

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Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Wellness