AI ENGINEER at Barker Staffing Solutions, LLC in New York, New York, United States

Job description

• We're looking for a talented and ambitious machine learning engineer with 5+ years of experience building production AI systems who's excited to tackle one of the toughest challenges in healthcare: automatically resolving claim denials. You'll be the technical lead for their agentic AI platform that autonomously researches, understands, and resolves insurance claim denials, helping healthcare practices recover millions in lost revenue.
• Insurance claim denials cost healthcare practices $125 billion annually, and resolving them requires deep expertise in medical billing, payer rules, and claim documentation. Today, billing managers spend hours manually researching each denial, gathering supporting documentation, and crafting appeals. We're building an agentic AI system that automates this entire workflow - from denial classification and root cause analysis, to evidence gathering and appeal letter generation.
• As a machine learning engineer, you'll architect and build the intelligent agents that power this system. You'll design multi-agent workflows that collaborate to interpret complex denial reasons, retrieve relevant clinical and billing information through RAG systems, reason about payer policies, and generate compelling appeals. This is a greenfield opportunity to build a production agentic system that will directly impact the financial health of healthcare practices.
• You should be comfortable (and excited!) about working in a fast-paced, early-stage startup environment where you can wear many hats and take on new challenges as they arise. This is a great opportunity for someone who wants to work on a highly challenging project at the intersection of AI and healthcare.
• THIS ROLE IS FULL-TIME. We're looking for candidates based in NYC. NO RELOCATION

Responsibilities

• Design and build the architecture for our agentic AI system that autonomously resolves insurance claim denials
• Develop specialized AI agents for denial classification, root cause analysis, evidence retrieval, policy reasoning, and appeal generation
• Implement multi-agent orchestration frameworks that coordinate complex workflows across research, decision-making, and document generation
• Build and optimize RAG systems to retrieve relevant clinical documentation, billing records, and payer policy information
• Create evaluation frameworks and feedback loops to continuously improve agent performance and reliability
• Design prompt engineering strategies and fine-tuning approaches to optimize LLM behavior for healthcare billing workflows
• Work closely with billing managers to understand denial resolution workflows and translate them into agent behaviors
• Collaborate with the engineering team on production infrastructure for deploying and monitoring AI agents at scale
• Actively contribute to building the team's AI/ML vision and technical roadmap
• Collaborate on code reviews and technical design documents to ensure code quality and distribute knowledge

Requirements

• You're passionate about Healthcare AI/ML – you want to solve real, pressing problems for providers and put them in control of their businesses. You naturally empathize with users and enjoy designing solutions with their needs in mind.
• You're excited to shape the future of our engineering team and lead by example – as an early team member, you'll have the chance to influence everything from our technical roadmap to our company culture. You have a radical sense of ownership with the ability and desire to own technical roadmaps and refine ambiguous problems. You also have a low ego, a growth mindset, and a desire to see the product and team scale with your impact.
• You have a love for your craft and strong technical execution - You view coding as a craft, not just a task, and you're excited about using technology to create meaningful impact. Your technical skills go beyond coding; you care about building a product that works at scale, with the user at the forefront.
• Must have 5+ years of experience in machine learning engineering, with a focus on building production AI systems and deploying models at scale.
• Strong experience with machine learning frameworks (PyTorch, TensorFlow, or JAX)
• Experience working with healthcare data or understanding of medical billing workflows is a plus
• Python and modern ML frameworks (PyTorch, TensorFlow, or JAX)
• LLM technologies, including prompt engineering, fine-tuning, and RAG systems
• Vector databases and semantic search systems
• Building reliable, production-grade AI systems with proper evaluation and monitoring
• MLOps practices, including model versioning, A/B testing, and performance tracking
• Working with APIs and integrating AI systems into broader product workflows

Skills

Required

• Python
• PyTorch
• TensorFlow
• JAX
• Vector databases
• Semantic search systems
• Building production-grade AI systems
• Working with APIs

Preferred

• Experience with healthcare data

Benefits

• Joining a meaningful team means the opportunity to make a direct, meaningful impact on clinicians' lives and the financial health of their practices. Here's what you can expect from working with us:
• Meaningful Impact You'll be tackling one of the most complex challenges in healthcare, helping practices thrive in a chaotic financial landscape. Your work will directly help solve one of the most hair-on-fire problems for providers, ensuring they can focus on what they do best: caring for patients.
• Autonomy & Ownership As an early team member, you'll have significant autonomy and the chance to shape our company from the ground up. You'll have ownership over your work and the freedom to challenge the status quo in an environment that values initiative and creativity.
• Growth & Learning We're a small, ambitious team with big goals, which means you'll be constantly learning and growing. You'll take on new challenges, expand your skill set, and have direct access to experienced founders and advisors who are invested in your development. We also offer stipends for professional development courses & books (which we often take together!) so we can all continue to grow.