Role Description Roger is an AI platform that frees home health clinicians from paperwork so they can focus on what matters: delivering life-changing care to our most vulnerable elderly patients in the comfort of their homes. We are now looking for a Senior Applied AI Engineer to build the intelligence layer at the core of Roger. - Train and fine-tune open source models, leveraging our vast proprietary dataset to push accuracy beyond what off-the-shelf models can do. - Build eval datasets and pipelines that let us measure model accuracy rigorously and improve it continuously. - Design how we measure accuracy: the metrics, harnesses, and feedback loops that turn real clinical outcomes into measurable model improvements. - Build scalable, cost-efficient inference infrastructure with great monitoring and observability. - Build better agentic infrastructure and partner on the interfaces that turn model capability into a great clinician experience. - Stay at the frontier: keep up with the latest research, frontier model capabilities, and open source frameworks, and bring the best of it into production. - Prototype quickly, then harden into scalable, secure, and reliable production systems. Qualifications - 7+ years of professional software engineering experience, with meaningful depth in AI/ML. - Experience training, fine-tuning, or evaluating LLMs and open source models, with real opinions about what works and what does not. - Shipped real AI software to real users. You can describe something you built, what broke, and how you fixed it. - Strong instincts for evals, observability, and the feedback loops that turn user feedback into measurable improvement. - Experience building agentic systems: tool use, generator and critic loops, planners and executors, and orchestration where one agent's output drives another's work. - Comfort building infrastructure that is fast, reliable, and cost-efficient at scale. - Startup experience shipping real features in high-growth environments. - A product mindset, comfort across the stack, and the ability to operate in ambiguity without a clean spec. - High standards for reliability and accuracy when real clinicians and patients depend on your work. Benefits - 🏥 Platinum health, dental, and vision insurance - 🏖️ Flexible PTO - 🤖 Be at the forefront of LLM innovation in healthcare - 🚀 Founded by AI Researchers from Cornell and Amazon Alexa - 👩‍⚕️ Make a tangible difference in the lives of clinicians and patients - 🧠 Work on a mission that matters, backed by AI innovation and top-tier investors Company Description If you're interested in joining a fast-growing healthcare AI startup, we'd love to hear from you TODAY! In person and remote opportunities available.

• Own and operate the AIDLC — Sphera's agentic software delivery framework that applies across all engineering, not just AI projects. • Serve as the senior technical practitioner within the AI COE — personally designing, building, and guiding AI solutions from concept through production across the portfolio. • Establish and enforce the defined delivery roles across squads — ensuring each role operates within its scope and that agentic execution is properly supervised and validated at every stage. • Drive adoption of the AIDLC operating model across engineering teams — onboarding squads, enforcing framework discipline, and intervening where teams drift toward ad-hoc approaches or accumulate governance gaps. • Create and apply AI solution evaluation frameworks — covering prompt quality, model accuracy, latency, cost, and production reliability — and monitor deployed features for drift and degradation. • Evaluate and benchmark emerging AI tools, models, and frameworks through structured experimentation, producing clear technical recommendations from hands-on testing. • Collaborate fluidly with engineering, product, InfoSec, Legal, and senior leadership, translating technical depth and business consequence depending on the audience.

• Enable scalable AI capabilities by structuring, organizing, governing, and maintaining knowledge assets • Create and sustain a centralized, reliable, and reusable knowledge base • Audit and consolidate knowledge assets to improve accessibility • Capture institutional and tribal knowledge during transition or integration • Establish governance and content architecture standards • Optimize knowledge assets for retrieval and AI enablement • Partner with stakeholders to keep knowledge current and relevant

• Design and develop interactive AI native front-end applications powered by AI Agents/LLMs • Create intuitive, AI-native user experiences that enable seamless interaction, collaboration, and control across Agentic AI systems and autonomous workflows • Partner with AI engineering / Data Science teams to integrate APIs, event driven (SSE),polling, webhooks and/or similar features • Prototype, design and implement modern Agentic UX standards, protocols and ideas , Ex. Elicitation, UX negotiation and A2UI compliant Apps • Build full stack AI Agents with Google ADK implementing advanced features like A2A, AAIF, A2UI, Agent skills, and MCP • Research and adopt modern full-stack technologies, Agentic UX innovations, and front-end best practices • Perform testing, debugging, optimization, and performance tuning to ensure high-quality user experiences • Partner with product managers, UX designers, and AI architects to translate business requirements into production-ready solutions