Regard
AI Engineer
Similar Jobs
Fintech • Machine Learning • Payments • Software • Financial Services
Lead design, development, deployment, and support of foundation model training and LLM inference platforms. Build similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for cost, latency, throughput, and scalability; contribute to technical vision and roadmap while partnering across engineering, research, product, and program teams.
Top Skills:
AWSAws UltraclustersAzureC#C++GoGCPHuggingfaceJavaLarge Language ModelsNemo GuardrailsPythonPyTorchScalaVectordbs
Fintech • Machine Learning • Payments • Software • Financial Services
Lead design, develop, deploy, and support foundational AI systems (LLM training/inference, similarity search, guardrails, observability). Partner cross-functionally to optimize scalability, cost, latency, and throughput, apply state-of-the-art research to production, and shape long-term AI platform roadmap.
Top Skills:
AWSAws UltraclustersAzureC#C++GoGCPHuggingfaceJavaNemo GuardrailsPythonPyTorchScalaVectordbs
.jpg)
AdTech • Cloud • Marketing Tech • Productivity • Software • Analytics • Automation
Design, build, and ship production-grade agentic AI workflows using LangGraph, Temporal, and Pydantic. Implement AI observability with LangFuse, set AI engineering standards (RAG, prompt management, tool-calling), benchmark LLMs, deploy cloud AI (containerization, cost management), and mentor engineers while supporting enterprise SLA, security, and compliance needs.
Top Skills:
AWSAzureCrewaiEmbedding ModelsGCPLangchainLangfuseLanggraphLlamaindexPydanticPythonRagTemporalVector Databases
As an AI Engineer at Regard, you’ll play a key role in developing and deploying AI-powered features that enhance physician workflows and improve patient care. You’ll be instrumental in integrating large language models into our platform—building scalable, reliable systems that deliver real value in clinical settings. Working closely with product, design, and engineering teammates, you’ll help prototype, implement, and refine innovative features that push the boundaries of what’s possible in healthcare.
Your primary focus will be on building and maintaining production-grade AI systems using best practices—leveraging tools like LangChain, vector databases, and retrieval-augmented generation techniques. You’ll bring hands-on experience in prompt engineering and LLM development, helping the team accelerate feature delivery and deepen our AI capabilities.
In this role, you’ll also contribute to a culture of learning by sharing practical insights and collaborating closely with teammates. You’ll have the opportunity to grow your own expertise while helping the team move faster and build smarter, more reliable systems.
About Regard
Our mission is to bring world-class healthcare to everyone. Regard is the world’s first comprehensive, automated diagnosis tool. Regard streamlines clinical and revenue cycle efforts to dramatically improve hospital finances, patient safety, and physician happiness. We are excited by challenges, mission-oriented work, and meaningful relationships. We work closely with some of the top health systems in the country and are leading the change that healthcare - one of the largest and most inefficient industries in the world - needs. We want you to join us.
Responsibilities:
- Lead the design and implementation of production-grade AI systems and tooling
- Architect and deploy AI systems using frameworks like LangChain, vector databases, RAG techniques and prompt management, tracing, and benchmarking tools
- Perform prompt engineering to optimize the output for LLM-based tasks, modify LLM system designs to add more functionality or improve the performance of our AI agents or tasks
- Mentor and level up engineering team members on AI agent development, system design, and production AI best practices
- Design architectures that improve end-user response times and reduce both algorithmic and AI-based latency and cost using appropriate prompting techniques
- Collaborate with product and design teams to rapidly prototype and iterate on AI-powered features while maintaining engineering quality standards
- Own end-to-end delivery of AI systems, from conception through production, deployment, and monitoring
- Navigate technical ambiguity and make architectural decisions that balance speed to market with system reliability and scalability
Qualifications:
- BS in Computer Science or equivalent experience
- 4+ years of software engineering experience with demonstrated ability to build and ship products end-to-end
- 1.5+ years of hands-on applied AI experience, including extensive work with OpenAI or Anthropic LLMs in production settings
- Demonstrated proficiency in Python
- Proven experience building AI agents with expertise in prompt engineering, LLM pipelines, and optimization of latency, cost, and quality
- Experience with retrieval-augmented generation, context window optimization, chunking, semantic search, vector databases, and other technologies used in conjunction with LLMs
- Strong mentoring and teaching abilities to level up team members on AI system design and implementation
Preferred Qualifications:
- Exposure to startup and/or high growth environments
- Background in ML techniques, including fine-tuning of models/LLMs and building evaluation and training datasets
- Experience in healthcare technology or other highly regulated industries
- Experience working with health technology
- Experience with machine learning systems, including building evaluation, training, and inference pipelines, and deploying custom-built ML models
Hybrid Work | Location | Work Authorization
- For this role, Regard is currently only considering candidates who are authorized to work in the US without visa sponsorship, and are within the New York City metro area
- We expect our Engineers to be in the office on Tuesdays and Thursdays. We may request more frequent in-office work during the onboarding period
- We will provide relocation assistance to anyone who does not already reside in the NYC metro area
- For those who enjoy working from our Manhattan office on a more regular basis, we offer catered lunches and other fun perks
- Additionally, hybrid employees have the flexibility to work from locations outside of their home office from up to 6 weeks per year
Comp | Perks | Benefits
- Eligible for equity
- 99% employer paid health benefits (Medical, Dental, and Vision) + One Medical subscription
- 18 PTO days/yr + 1 week holiday break
- Annual $750 learning & development stipend
- Company-sponsored team retreat + social events
- A sabbatical program
Our goal at Regard is to provide and maintain a work environment that fosters mutual respect, professionalism and cooperation. Regard is proud to be an equal opportunity employer that does not discriminate on the basis of actual or perceived race, creed, color, religion, national origin, ancestry, alienage or citizenship status, age, disability or handicap, sex, gender identity, marital status, familial status, veteran status, sexual orientation or any other characteristic protected by applicable federal, state or local laws. We celebrate diversity and are proud of our supportive, inclusive workplace.
All candidates must successfully complete a background check as part of the hiring process.
Regard New York, New York, USA Office
432 Park Avenue South, New York, NY, United States, 10016-8010
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
