Direct Recruiters Inc.
Overview
Client Summary: Specialized AI tools designed specifically for healthcare workflows Helps healthcare teams interpret and organize unstructured information like notes, claims, and documents Reduces manual work and improves decision-making efficiency across clinical and administrative tasks Supports organizations such as health insurers, providers, and medical research groups Demonstrated impact on care management speed, error reduction, and compliance reporting Tailored to understand complex medical language and systems Enables faster, more accurate reviews and operational performance without generic AI limitations Position Responsibilities
Technical Leadership & Strategy
Define and evolve our platform and product roadmap aligned with business priorities and customer expectations Guide architectural decisions across ML pipelines, APIs, and enterprise integrations Work closely with leaders to collaborate and execute on the product vision Be a partner to Product and sales/go-to-market leaders to align platform investments with business outcomes. Own infrastructure scalability (Kubernetes on various clouds), data security, and compliance (HIPAA, HITRUST, SOC2) working with CISO
Team Building & Execution
Own and evolve a high-leverage engineering org structure that scales across geographies and product lines. Oversee best-in-class processes across CI/CD, code quality, information security, and observability to realize AgentOps lifecycle Establish a release cadence by shipping product releases on a regular basis Identify and grow technical leaders, create pathways for autonomy, and eliminate process friction. Partner with customer solutions and forward deployment teams to accelerate delivery of product capabilities without sacrificing quality and stability Build for resiliency and scale in mind — not just speed. You reduce toil through automation and uplift long-term system health.
Collaboration & Representation
Act as the face of Engineering with strategic customers, demonstrating deep platform knowledge and inspiring confidence Understand customer infrastructure needs into scalable product capabilities that can be easily configured for customer deployments Ensure our platform can support high-volume clinical workflows, interoperability, and analytics by creating and testing capabilities Align GTM, Product, and Customer Ops to ensure delivery excellence and rapid iteration on feedback
Experience & Skills
Required Experience and Qualifications: 10+ years of engineering experience, including 5+ in leadership roles building enterprise Data and AI systems Built and led teams working with healthcare payers and/or large provider systems in a fast-paced setting like startups Deep understanding of enterprise healthcare infrastructure, ML and data pipelines, and APIs (e.g. HL7, FHIR, EHR integrations), Application integration such as QNXT, Pega, Salesforce Strong track record of shipping secure, compliant, production-grade software in health tech Technical Knowledge & Deep Expertise
Prior experience in AI/ML infrastructure or knowledge automation using Agentic AI and Generative AI technologies and frameworks Working knowledge of Generative AI patterns such as RAG, GraphRAG as well as prompt engineering best practices Familiar with tools Kubernetes, Keda, Kafka, Agentic AI frameworks like LangGraph, Langchain, LlamaIndex, database technologies including fitment of product needs, and modern DevSecOps stacks Help with navigating enterprise security, info sec. audits and vulnerabilities by automating common DevSecOps processes within the toolchain Deep expertise is setting up scalable workload configurations in Kubernetes using common best practices such as pod and node autoscaling
Efficiency & Streamlined Processes
Review and optimize costs on infrastructure spend by creating dashboards with visibility into real-time spend metrics across SaaS and internal environments. Optimize spend by evaluating instance types, GPU instances, execution patterns such as batch jobs for long running processes Ensure faster installation of our platforms using IaC best practices such as Helm, Terraform automation resulting to a one-click deployment option or developing Agents Streamline environments from creation to de-commissioning them across internal and customer environments Establish quality gates from developer workstations to build systems using known tools such as Pylint, Pytest, SonarCube, Snyk
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Client Summary: Specialized AI tools designed specifically for healthcare workflows Helps healthcare teams interpret and organize unstructured information like notes, claims, and documents Reduces manual work and improves decision-making efficiency across clinical and administrative tasks Supports organizations such as health insurers, providers, and medical research groups Demonstrated impact on care management speed, error reduction, and compliance reporting Tailored to understand complex medical language and systems Enables faster, more accurate reviews and operational performance without generic AI limitations Position Responsibilities
Technical Leadership & Strategy
Define and evolve our platform and product roadmap aligned with business priorities and customer expectations Guide architectural decisions across ML pipelines, APIs, and enterprise integrations Work closely with leaders to collaborate and execute on the product vision Be a partner to Product and sales/go-to-market leaders to align platform investments with business outcomes. Own infrastructure scalability (Kubernetes on various clouds), data security, and compliance (HIPAA, HITRUST, SOC2) working with CISO
Team Building & Execution
Own and evolve a high-leverage engineering org structure that scales across geographies and product lines. Oversee best-in-class processes across CI/CD, code quality, information security, and observability to realize AgentOps lifecycle Establish a release cadence by shipping product releases on a regular basis Identify and grow technical leaders, create pathways for autonomy, and eliminate process friction. Partner with customer solutions and forward deployment teams to accelerate delivery of product capabilities without sacrificing quality and stability Build for resiliency and scale in mind — not just speed. You reduce toil through automation and uplift long-term system health.
Collaboration & Representation
Act as the face of Engineering with strategic customers, demonstrating deep platform knowledge and inspiring confidence Understand customer infrastructure needs into scalable product capabilities that can be easily configured for customer deployments Ensure our platform can support high-volume clinical workflows, interoperability, and analytics by creating and testing capabilities Align GTM, Product, and Customer Ops to ensure delivery excellence and rapid iteration on feedback
Experience & Skills
Required Experience and Qualifications: 10+ years of engineering experience, including 5+ in leadership roles building enterprise Data and AI systems Built and led teams working with healthcare payers and/or large provider systems in a fast-paced setting like startups Deep understanding of enterprise healthcare infrastructure, ML and data pipelines, and APIs (e.g. HL7, FHIR, EHR integrations), Application integration such as QNXT, Pega, Salesforce Strong track record of shipping secure, compliant, production-grade software in health tech Technical Knowledge & Deep Expertise
Prior experience in AI/ML infrastructure or knowledge automation using Agentic AI and Generative AI technologies and frameworks Working knowledge of Generative AI patterns such as RAG, GraphRAG as well as prompt engineering best practices Familiar with tools Kubernetes, Keda, Kafka, Agentic AI frameworks like LangGraph, Langchain, LlamaIndex, database technologies including fitment of product needs, and modern DevSecOps stacks Help with navigating enterprise security, info sec. audits and vulnerabilities by automating common DevSecOps processes within the toolchain Deep expertise is setting up scalable workload configurations in Kubernetes using common best practices such as pod and node autoscaling
Efficiency & Streamlined Processes
Review and optimize costs on infrastructure spend by creating dashboards with visibility into real-time spend metrics across SaaS and internal environments. Optimize spend by evaluating instance types, GPU instances, execution patterns such as batch jobs for long running processes Ensure faster installation of our platforms using IaC best practices such as Helm, Terraform automation resulting to a one-click deployment option or developing Agents Streamline environments from creation to de-commissioning them across internal and customer environments Establish quality gates from developer workstations to build systems using known tools such as Pylint, Pytest, SonarCube, Snyk
#J-18808-Ljbffr