Principal Engineer

Position: Staff / Principal Engineer
Staff / Principal Engineer

Department: Advisory

Employment Type: Full Time

Location: US

Compensation: $163,547 - $185,000 / year

Description

Newfire Global Partners is a leading technology firm that specializes in building transformative software solutions for some of the world's most innovative companies. With a presence across four continents, Newfire Global brings deep expertise in digital healthcare, AI-driven analytics, and enterprise technology. The firm's track record of delivering scalable, high-impact solutions has made it a trusted partner for organizations seeking to drive meaningful change through technology.

We are passionate about the purpose-driven mission to help improve the quality of care for patients and are building a collaborative, innovative, and inclusive culture. We are a fully funded company founded by serial entrepreneurs with a stable client base.

Opportunity for impact

Newfire Global Partners, a leader in developing disruptive healthcare technology, collaborates with Fortune 500 companies and start-ups to drive transformation.

We are seeking an exceptional Staff or Principal Engineer to join our client's engineering leadership team. This is a senior individual contributor role for a technologist who thrives at the intersection of modern software engineering and artificial intelligence. The ideal candidate will bring deep full-stack expertise across C#, React, and Python, paired with a demonstrated ability to lead and champion AI-assisted development practices-spanning LLM integration, MLOps, prompt engineering, and AI-powered product features.

Based in the US with a strong preference for East Coast availability, this engineer will set the technical direction for how AI amplifies our engineering teams and shapes our healthcare platform

Role & responsibilities

• Serve as a technical leader and trusted authority on AI-assisted engineering, driving adoption of Copilot, code generation, and LLM-powered tooling across the engineering organization.

• Architect and deliver AI-powered product features that improve healthcare outcomes-spanning intelligent automation, clinical decision support, and member-facing experiences.

• Design and implement LLM workflows and prompt engineering patterns, ensuring reliable, safe, and scalable AI integrations in production environments.

• Lead MLOps initiatives including model deployment pipelines, monitoring, versioning, and lifecycle management in collaboration with data science teams.

• Build and maintain full-stack solutions using C# (.NET), React, and Python, with a strong focus on scalability, security, and maintainability.

• Define and evangelize engineering best practices for AI integration, code quality, and system design across Staff and Senior engineers.

• Collaborate with product, data, and clinical teams to identify high-impact opportunities for AI and machine learning in the healthcare domain.

• Conduct design reviews, architecture discussions, and hands-on code reviews to raise the technical bar across the organization.

• Mentor and grow senior engineers, fostering a culture of experimentation, ownership, and continuous learning.

• Stay at the forefront of rapidly evolving AI/ML tooling, evaluating and recommending emerging technologies relevant to the client

You're a Perfect Match If You Have:

• Deep proficiency in C# and .NET - including API design, microservices architecture, and enterprise-grade backend systems.

• Strong hands-on experience with React and modern front-end development patterns (Type Script, component architecture, state management).

• Solid Python skills with practical experience in scripting, automation, data pipelines, or ML model integration.

• Proven experience integrating LLMs (e.g., OpenAI, Azure OpenAI, Anthropic) into production applications via APIs, SDKs, or orchestration frameworks such as Lang Chain or Semantic Kernel.

• Strong understanding of prompt engineering principles, RAG (Retrieval-Augmented Generation) patterns, and LLM evaluation strategies.

• Hands-on experience with MLOps tooling and practices - model versioning, deployment, monitoring, and retraining pipelines.

• Experience with AI-assisted development…