AI Model Engineer - Remote/Nationwide

This is a remote based position. Applicants can be located nationwide

Back 34d AI Model Engineer #2715 United States Apply X Facebook LinkedIn Email Copy Position Description

About You

You are a person who is passionate about serving as a core technical leader within the Innovation, Research & Development (IR&D) department. We need someone who is responsible for architecting, optimizing, and operationalizing advanced AI systems that power Signature Performance's WorkflowXM platform, agentic workflow automation tools, and AI-enabled healthcare administrative solutions. In the role of AI Model Engineer, you will design, fine-tune, evaluate, and deploy large language models (LLMs), multimodal models, retrieval systems, and agentic frameworks that support high-volume medical coding, billing, claims processing, health insurance discovery, eligibility verification, customer service support, EDI ingestion, and enterprise automation.

• Tell us about your experience with AI Model Engineering.
• Are you a team player and a self-motivator?
• We are counting on you to manage multiple projects using your problem-solving skills.
• We are looking for someone UNCOMMON. What is uncommon about you?

Are you highly committed? Are you team-oriented? Do you value professionalism, trust, honesty, and integrity? If so, we cannot wait to meet you.

About The Position

AI Model Development & Optimization (40%)

• Design, fine-tune, distill, and optimize LLMs and multimodal models to support WorkflowXM and other enterprise AI initiatives.
• Implement PEFT/LoRA/Q-LoRA fine-tuning strategies for domain-specific healthcare tasks.
• Develop retrieval-augmented generation (RAG) pipelines using vector databases (e. g. , Qdrant).
• Architect and evaluate model prompting frameworks, system prompts, and agentic prompt templates.
• Optimize inference speed, accuracy, grounding, and reliability across on-prem and cloud environments.

Agentic AI System Engineering (25%)

• Build and maintain tool-using AI agents, orchestrators, governance watchdog agents, and multi-agent workflows.
• Implement memory systems, shared context, scratchpads, tool-calling logic, and verification loops.
• Integrate AI agents with internal systems, including MCP servers, WorkflowXM modules, backend microservices, and data ingestion pipelines.
• Create reusable "AI capability modules" for insurance discovery, claims QA, coding assistance, EDI parsing, and document understanding.

Model Evaluation, Guardrails & Compliance (15%)

• Develop evaluation datasets, synthetic tests, and red-teaming harnesses for model quality assurance.
• Implement guardrails for PHI/PII protection, hallucination minimization, and HIPAA-compliant behavior.
• Monitor model drift, regressions, latency metrics, and accuracy degradation.
• Work closely with IR&D governance and security partners to align models with Data Ethics & AI Governance Policy (CCP-046).

AI Infrastructure & Deployment Support (10%)

• Collaborate with AI Systems Engineers and DevOps to deploy, containerize, and scale models in production.
• Support GPU/accelerator utilization strategy and model serving frameworks (vLLM, Ollama, HuggingFace, TensorRT-LLM).
• Assist in designing and maintaining model registries and versioned deployment systems.
• Ensure high-throughput, high-availability inference services for WorkflowXM and enterprise applications.

Cross-Functional Collaboration & Innovation (10%)

• Partner with analysts, developers, QA, clinical SMEs, and business stakeholders to translate operational needs into AI capabilities.
• Contribute to AI-driven modernization of claims processing, revenue cycle workflows, EHR optimization, and payer service operations.
• Support rapid prototyping, experimentation, and innovation aligned with IR&D's strategic priorities.
• Document architectural approaches, model behaviors, and best practices for internal knowledge growth.

Minimum Requirements:

Education & Experience

• Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Applied Mathematics, or related field (or equivalent experience).
• 3-7+ years of hands-on experience designing, training, or deploying machine learning or deep learning models.
• 2+ years of direct experience with large language models, transformer architectures, or agentic AI systems.

Technical Skills

• Strong proficiency with Python, PyTorch, HuggingFace Transformers, LangChain/LlamaIndex, and vLLM or similar inference engines.
• Expertise in fine-tuning, PEFT/LoRA tuning, prompt engineering, and RAG architectures.
• Experience deploying models using Docker, Kubernetes, GPU/TPU compute environments, and model-serving frameworks.
• Hands-on experience with vector databases (e. g., Qdrant), embeddings, and semantic search.
• Understanding of NER, NLP, document processing, and multimodal ingestion (audio, text, PDF, EDI).
• Ability to build agent-based systems with tool-calling, planning, verification loops, and chain-of-thought scaffolding.

Preferred Requirements:

Healthcare Domain Knowledge

• Experience with health insurance, payer portals, COB/OHI logic, medical billing, claims processing, medical coding, or EDI/HL7/FHIR standards.
• Understanding of HIPAA, PHI/PII handling, and secure AI practices.

Soft Skills

• Strong problem-solving and analytical mindset.
• Ability to work in fast-paced environments with ambiguous requirements.
• Clear communication skills for collaborating with technical and non-technical stakeholders.