X4 is partnering with a growing healthcare AI company that develops intelligent software for healthcare organizations. Its products use machine learning, generative AI, and AI agents to simplify complex clinical and administrative work, helping teams make faster, better-informed patient care decisions.

The company prioritizes explainability, security, and human oversight in its AI solutions and is investing in the growth of its AI engineering team.

About the Role

The company is seeking a Principal AI/ML Engineer to shape and lead its AI engineering strategy. This is a senior, hands-on position responsible for setting the technical direction across AI, machine learning, generative AI, and agentic automation, while guiding solutions from architecture and design through production deployment.

Much of the work supports a US government healthcare agency, involving the development of secure, reliable AI systems that improve services at scale. You will collaborate with engineering, product, and agency stakeholders while influencing the platform architecture, engineering standards, and future growth of the team.

Key Responsibilities

Define AI/ML and generative AI architecture and engineering strategy.

Design scalable, reliable systems for machine learning, deep learning, LLMs, RAG, multimodal AI, and AI agents, covering backend architecture, system design, and some frontend capability.

Establish development, inference, evaluation, observability, and governance standards.

Evaluate emerging AI platforms, make build-versus-buy decisions, and create reusable frameworks for the wider engineering team.

Architect single-agent and multi-agent solutions to automate operational workflows.

Design event-based architectures for high-volume document processing pipelines, including triggering, orchestration, summarization, structured data extraction, and database persistence.

Implement guardrails, authorization controls, and human-in-the-loop processes.

Lead the delivery of production-grade LLM and machine learning applications, including LLM-driven applications and RAG solutions.

Own model selection, prompt engineering, and optimization strategies.

Develop approaches for LLM output evaluation, hallucination reduction, accuracy measurement, and LLM-as-judge patterns.

Address challenges involving bias, data leakage, and prompt injection.

Define workload requirements, including throughput, SLAs, traffic patterns, and scalability for batch and continuous processing.

Establish MLOps and LLMOps practices and design cloud deployment architectures.

Implement monitoring, observability, versioning, and rollback processes.

Mentor engineers, lead design and architecture discussions, conduct code reviews, and define the AI roadmap and proofs of concept.

Required Qualifications

10+ years of software engineering or AI/ML experience.

Deep full-stack engineering experience, including backend architecture, system design, scalability, and reliability, along with some frontend capability.

Hands-on experience with AI/LLM systems, agentic AI, LLM-driven applications, document processing pipelines, and production-grade AI solutions.

Ability to demonstrate technical depth through systems designed and delivered.

Experience designing event-based architectures for high-volume, real-time, or batch document processing, including triggering, orchestration, summarization, structured extraction, and data persistence.

Strong problem-solving skills, including the ability to clarify and challenge requirements involving throughput, SLAs, traffic patterns, and scalability before selecting an architecture.

Solid understanding of LLM evaluation, including hallucination reduction, accuracy measurement, LLM-as-judge, and multi-LLM consensus approaches.

Strong hands-on Python experience and knowledge of machine learning, LLMs, cloud platforms, MLOps, and security.

Experience with MS SQL Server, including writing queries, designing schemas, and tuning performance.

Bachelor’s or master’s degree in a related field, such as data science, machine learning, or computer science.

US citizenship.

Preferred Qualifications

Active security clearance.

Experience working in healthcare.

Claude Certified Architect certification.

Experience with PyTorch, TensorFlow, scikit-learn, LangGraph, LangChain, OpenAI, Azure OpenAI, Anthropic, and Gemini models.

Location and Work Arrangement

Remote position with occasional in-person attendance.

Salary and Benefits

Competitive salary.

Healthcare.

401(k).

Bonus.

Application Contact

To apply or recommend someone for the position, contact o.archer@x4lifesciences.com.

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