Role Description Onpoint Healthcare Partners builds Iris, a Medical Agent AI platform that takes administrative work off the plates of providers and care teams. Our agents handle charting, coding, care gap closure, and care coordination across the full patient journey, combining AI automation with expert clinical oversight. More than 2,000 providers across 35+ specialties rely on the platform every day, which means the systems behind it have to be accurate, reliable, and auditable without exception. We are seeking a Staff AI Engineer to design, build, and scale the agent systems behind Iris. This role combines strong software engineering fundamentals with deep experience building production AI systems. The work you ship directly determines how much time providers get back for patient care. The ideal candidate has shipped AI solutions to production that deliver measurable business value, and will evolve and be a good steward of the agent platform architecture. Key Responsibilities - Design and develop AI applications and agent workflows. - Build scalable backend services, APIs, and integrations supporting AI solutions. - Evolve and steward the agent platform architecture, including orchestration, runtime safety, and prompt governance. - Treat prompts and tool schemas as versioned code with staged rollouts and rollback. - Develop and maintain evaluation frameworks for AI agents and models, with CI gates that block bad changes before release. - Design retrieval, memory, and context management strategies. - Build observability, monitoring, and debugging capabilities, including full trace and replay for incident resolution. - Build the MLOps foundation the team is currently missing: training and retraining pipelines, model versioning, model registry, and feature stores, so model work stops being reactive. - Stand up A/B testing infrastructure and automated drift detection that triggers retraining, so model quality is monitored and maintained without manual firefighting. - Track token and tool costs per run, workflow, and tenant, and keep costs predictable as usage scales. - Improve reliability, performance, safety, and cost efficiency of production AI systems. - Partner with Product, Clinical, Data Science, and Engineering teams to deliver AI capabilities. - Own AI deployment, monitoring, and operational excellence. Qualifications - 8+ years of software engineering experience. - 3+ years building AI and ML applications. - Strong Python and/or C# development experience. - Experience deploying AI systems into production environments. - Experience with LLMs, RAG architectures, agent frameworks, and AI evaluation. - Experience with AWS and distributed systems. - Hands-on experience building MLOps infrastructure such as training pipelines, model registries, feature stores, A/B testing, and drift detection. - Strong debugging, observability, and operational skills. Preferred Qualifications - Healthcare industry experience. - Experience with HIPAA, PHI, and regulated environments. - Experience with vector databases, embeddings, and knowledge graphs. - Experience building AI systems at large scale. Success Metrics - Reliable, scalable, and cost efficient AI systems running in production. - Incidents get resolved fast because tracing and replay make root cause obvious. - Cost per workflow stays predictable as volume grows. - Model training, versioning, and retraining run as a managed pipeline rather than a reactive, manual effort. - Strong adoption and measurable business impact. - High trust in AI quality, safety, and operational performance. Physical Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to speak, hear, read, and type. This is largely a sedentary role. This position requires the ability to occasionally lift office products and supplies up to 40 pounds. Work Environment To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed above are representative of the knowledge, skill and/or ability required. Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time, with or without notice.

• Projetar, desenvolver e manter **APIs, SDKs e serviços de plataforma**. • Implementar integrações e camadas de orquestração para agentes e serviços de IA. • Garantir **segurança, performance e observabilidade** em sistemas distribuídos em cloud. • Colaborar com squads multidisciplinares, apoiando decisões técnicas e evolução da arquitetura. • Contribuir para a melhoria contínua de pipelines CI/CD e práticas de **DevOps/Infra as Code**. • Participar de discussões técnicas, propondo soluções alinhadas a boas práticas de engenharia. • Apoiar e orientar desenvolvedores menos experientes, fortalecendo a cultura de qualidade.

Role Description Serious Development is a boutique healthcare strategy, product, and software engineering firm. We partner with healthcare organizations to solve complex operational challenges through thoughtfully designed custom software. We are actively seeking a full-stack AI/ML Software Engineer to help us build HealthTech apps and systems for our clients by contributing as a member of one of our agile engineering teams. Responsibilities include: - Implement scalable microservices that will work in concert together as applications. - Shape pieces of technical architecture and integrate our applications with ML & third-party technologies. - Enhance existing features and participate in code reviews. - Help ensure that the team is delivering high quality code and optimize existing systems. - Become an SME and owner of some of the services and systems that you helped implement. - Contribute your experience to make your team and the department stronger. Qualifications - Bachelor of Science degree in Computer Science, Computer Engineering, Software Engineering, or similar engineering major. - 4+ years of experience as an AI/ML Software Engineer with same/similar responsibilities (excludes any internship experience). - Experience engineering with Python. - Experience engineering in Linux and/or MacOS environments. - Experience engineering a SaaS product/platform. - Experience accurately logging all design, development, and consulting hours daily to prevent revenue leakage and ensure precise client invoicing. - Excellent written and verbal communication skills (English Level at least C1- Advanced). - Role based in Europe. - Must have valid work authorization and residency in Europe. Requirements - Operate as a self-sufficient, T-shaped, full-stack AI/ML engineer. - Recommend AI/ML-driven solutions and implement them. - Review technical architecture documentation for the project and ensure that the engineering team's deliverables are implemented accordingly. - Develop code that fulfills requirements specified by the business, technical architects, and clients. - Ensure that the code you deliver has an extremely high level of quality and extremely low potential for defects that will surface in the production environments. - Author documentation of your code that is useful for your team members and other members of Engineering. - Participate as a team-player that works together with your fellow team members to deliver commitments on time. - Dive into code as technical challenges arise to perform root-cause analyses and implement resolutions. - Develop proofs of concepts as needed. - Review code written by your team members to help catch issues before they surface after deployment. - Keep current with engineering best practices, design principles, technology, security, and compliance to apply that knowledge to all the responsibilities above. Benefits - Working proficiency of Portuguese, Spanish, or Ukrainian language skills could be helpful.

• Lead a team of Product Managers across AI Platform, Analytics, Portals, and Platform/Integrations • Set strategy and ladder to the 2026 GA calendar and 2028 vision • Own the AI Platform and agent strategy • Partner with engineering on AI architecture decisions • Define outcomes and articulate measurable customer and business outcomes