AI Engineering Lead

Open role

• Engineering AI Engineering Lead

Beni Health Remote

• US-Based Full-time Early-stage equity Reports to VP of Product and Engineering Apply here

Most AI health companies are still pitching what they'll build. Beni is already live inside primary care practices, handling real patient interactions through cutting-edge voice AI and multi-modal messaging, coordinating care between visits, and generating revenue and meaningful clinical outcomes. We're hiring an AI forward engineering lead to help us take the product to the next level.

About The Role

This is a hands-on engineering role at a company transitioning from a strong AI-assisted product to a fully agentic one. You'll architect and build the systems that power Beni's next generation: multi-modal patient communication (voice, SMS, structured data), intelligent care coordination workflows, and the integrations that connect our platform to the clinical data that makes it useful.

You'll work across a founding team that includes highly regarded medical experts with deep expertise in the space, alongside an established, highly accomplished product, sales and operations executive team.

What You'll Own

• Architecture and implementation of Beni's agentic AI systems: orchestration, memory, tool use, multi-step reasoning
• The multi-modal communication layer, including our voice AI pipeline and asynchronous outreach channels
• EMR integration work, connecting Beni's intelligence to the clinical data that lives in practice systems (FHIR, HL7 and other applicable frameworks)
• Production reliability for AI outputs in a clinical context: evaluation frameworks, monitoring, and graceful failure handling
• Backend infrastructure that is scalable and provides the highest level of privacy and security
• Close AI native collaboration with the product team leveraging emerging technologies and workflows to accelerate shipping and deployment
• Code review, release process, and keeping dependencies patched across the services you own
• On-call rotation and incident response for production systems

Requirements And Qualifications

Minimum qualifications

• Bachelor's degree in Computer Science, Software Engineering, or a closely related technical field
• Five or more years of professional software engineering experience, including at least two years building and operating AI or machine learning systems in production
• Hands-on production experience with LLM application development: orchestration, retrieval-augmented generation, tool use and function calling, and multi-step reasoning
• Strong backend fundamentals, including the design and operation of APIs, asynchronous and event-driven systems, and data pipelines in Python and/or TypeScript
• Experience deploying and operating services on a major cloud platform (AWS, GCP, or Azure), including CI/CD, containerization, and infrastructure as code
• Demonstrated experience building systems that handle sensitive or regulated data, including encryption in transit and at rest, role-based access control, and audit logging
• Working at the cutting edge of AI, using emerging tools and frameworks to accelerate your daily work and your collaboration with the team
• Exceptional verbal and written communication, sufficient to work directly with clinicians and other non-technical stakeholders
• Proactive attitude and strong self-direction, focusing on progress over process
• Authorized to work in the United States; this role is remote but requires US residency

Preferred Qualifications

• Master's or doctoral degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
• Healthcare data and EMR integration experience: FHIR, HL7v2, and platforms such as Epic, athenahealth, or eClinicalWorks
• Working knowledge of HIPAA as it applies to engineering, and experience operating under a formal compliance program such as SOC 2 or HITRUST
• Real-time voice AI experience: speech recognition and synthesis, telephony (Twilio, LiveKit, SIP), and low-latency streaming pipelines
• Experience building evaluation and monitoring frameworks for non-deterministic model output
• Prior founding or lead engineer experience at an early-stage startup

Certifications

• No certifications are required for this role. Cloud or security certifications such as AWS Certified Solutions Architect, AWS Certified Security – Specialty, or CISSP are viewed favorably but are not a condition of hire.

The Opportunity

We're putting agentic AI to a real test. We have live patients, live practices, and a tight feedback loop between what we build and what actually happens in care. You'll be building an agent layer designed from the ground up to support continuous care between visits. This is an opportunity to create measurable impact in a high stakes environment.

This role is open to US-based applicants. Compensation includes early-stage equity. We're a small team building infrastructure for a problem that matters.

Interested?

Fill out our short application. It takes about 5 minutes.

Apply here