Role Description We are looking for an exceptional AI Architect to design, build, and optimize AI-driven applications on the Azure platform. This role emphasizes strong engineering expertise, creative problem-solving, and the ability to work with cutting-edge technologies to deliver high-impact solutions. The ideal candidate thrives on solving complex challenges, is passionate about engineering excellence, and has a knack for integrating AI into scalable, real-world applications. A background in data science or formal engineering is a strong advantage, given the scientific nature of the work. Key Responsibilities - Architect & Build: Design and implement AI applications leveraging Azure services (AKS, Azure Container Apps, Blob Storage, Document Intelligence, AI Studio/Foundry, VNETs). - Full-Stack Development: Develop systems using C#, Python, React, and modern frameworks like Entity Framework Core, LangChain, Semantic Kernel, and FastAPI. - Scalable & Secure Solutions: Create applications that are resilient, secure, and optimized for high performance. - Collaboration: Work closely with cross-functional teams, including data scientists and engineers, to turn abstract ideas into functional solutions. - Cloud-Native Focus: Lead the deployment and optimization of applications in Azure environments with strong consideration for cost efficiency and maintainability. - Innovate & Optimize: Explore new tools, frameworks, and methodologies to stay at the forefront of AI and software engineering. Qualifications - Proven expertise in software engineering with experience in C#, Python, and React (TypeScript). - Hands-on experience with cloud platforms, particularly Azure, including services like AKS, Networking, and AI Studio/Foundry. - Familiarity with AI frameworks like LangChain, Semantic Kernel, and other AI libraries or tools, as well as techniques such as RAG, Agentic patterns, and workflow orchestration. - Strong grasp of modern development practices, such as containerization, CI/CD, and API design. - Demonstrated ability to design and build secure, scalable, and maintainable systems. Preferred Skills - Background in data science or formal training in engineering disciplines. - Experience with frameworks like Entity Framework Core, Material UI, and FastAPI. - Understanding of AI modeling workflows and integration of document intelligence or related tools. Core Qualities - Problem-Solving Excellence: A creative and analytical approach to tackling technical challenges. - Ownership & Accountability: Ability to take full responsibility for the design, implementation, and success of projects. - Adaptability: Comfortable learning and implementing new technologies in a fast-evolving field. - Team Collaboration: Strong communication skills and a mindset that thrives in a team-driven environment. Company Description Nimble Gravity is a team of outdoor enthusiasts, adrenaline seekers, and experienced growth hackers. We love solving hard problems and believe the right data can transform and propel growth for any organization. Nimble Gravity is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Nimble Gravity considers all qualified applicants.

Role Description We’re looking for a Senior AI Engineer to join our Engineering team. This person will play a pivotal role in architecting and delivering privacy-first AI systems that power the next generation of Osano’s product capabilities. This role goes beyond wrapping APIs or building chat interfaces. You will: - Design and deploy autonomous AI agents - Develop strict-source-following RAG systems - Implement evaluation frameworks that ensure reliability, compliance, and production-grade performance This position is ideal for someone who is highly technical, thrives in ambiguity, takes ownership of 0→1 initiatives, and believes responsible AI development is non-negotiable. Responsibilities - AI System Architecture - Architect and deploy autonomous AI agents and multi-agent workflows - Design strict-source-following Retrieval-Augmented Generation (RAG) systems that minimize hallucination and enforce citation integrity - Implement guardrails, structured outputs, and validation layers - Production Engineering - Build scalable backend services using FastAPI - Orchestrate agentic workflows using LangGraph - Deploy and manage AI workloads within AWS or Azure - Optimize model performance, reliability, and cost - Evaluation & Continuous Improvement - Develop rigorous evaluation pipelines measuring: - Accuracy - Citation adherence - Latency - Reliability - Establish metric-driven iteration cycles - Continuously refine deployed systems based on measurable outcomes - Privacy-First Development - Embed privacy-by-design principles across the AI stack - Ensure compliance, data sovereignty, and secure handling practices - Collaborate cross-functionally to align AI capabilities with regulatory standards Qualifications - 5+ years of professional experience - Experience deploying and managing AI workloads in AWS or Azure - Deep technical understanding of LLM usage and orchestration beyond prompt engineering - Strong expertise in Python AI ecosystem, specifically: - FastAPI - LangGraph - Proven experience building: - Complex RAG systems - Autonomous AI agents - Experience building evaluation frameworks and iterating based on performance metrics Requirements - Experience with Knowledge Graphs to enhance RAG precision - Familiarity with Privacy-Enhancing Technologies (PETs) - Experience with data anonymization techniques - Background in compliance-heavy or regulated environments Benefits - Competitive-pay compensation and ownership interest/equity - Unlimited paid time off, plus a requirement to take at least two weeks off per year - We're a Best Place for Working Parents and offer paid parental leave for all new parents - Osano sponsors individual premiums on base plans at 100% and dependent premiums at 50% for Medical, Dental, and Vision insurance via Aetna - A fully and permanently remote company, so you can work from anywhere in the U.S. - Receive a MacBook and $600 to craft your home workspace - Annual company trip designed to foster connection, creativity, and fun - Mental health benefits with free memberships to mindfulness and talk therapy services

• Own the end-to-end voice AI architecture — from Twilio media streams through LLM orchestration to TTS output and call disposition. • Design and implement multi-agent systems using tool calling, agent handoffs, and shared conversation state for complex patient workflows. • Build and optimize real-time audio pipelines — WebSocket streaming, codec handling (mulaw/PCM), VAD configuration, and interruption management. • Architect analytics and observability infrastructure for voice-specific metrics: per-segment latency (STT/LLM/TTS), call efficacy, disposition accuracy, and ASR error rates. • Solve voice-specific challenges: turn-taking timing, silence detection thresholds, barge-in recovery, medical term recognition, and end-to-end latency optimization. • Integrate voice agents with internal services via secure authenticated APIs. • Drive platform reliability — eliminate single points of failure, implement multi-provider LLM failover, and design graceful degradation paths. • Collaborate with product and clinical operations to improve self-serve efficacy rates and reduce call escalations. • Mentor team members on voice AI best practices and contribute to architectural decisions.

• Take ownership of assigned voice AI features and components, guiding them through the full software development lifecycle. • Contribute to design discussions, code reviews, and best practice adoption within the Voice AI team. • Drive technical decisions on voice pipeline optimization — VAD tuning, turn-taking, interruption handling, and latency management. • Plan and prioritize tasks in an Agile environment, ensuring timely and high-quality delivery. • Work with Product Managers and stakeholders to refine requirements and scope technical efforts for conversational AI features. • Monitor voice platform health metrics (call efficacy, ASR accuracy, per-segment latency) and prioritize improvements based on data. • Mentor junior team members, sharing knowledge and best practices in voice AI architecture, TypeScript, and real-time systems. • Encourage a culture of continuous learning and technical excellence through pair programming and design reviews. • Document voice AI patterns, integration contracts, and operational runbooks for the team. • Partner with Product Managers, QA, and clinical operations to gather requirements, validate conversational designs, and guide projects from inception to deployment. • Coordinate with other engineering teams to integrate voice agents with internal services via authenticated APIs. • Work with the analytics team to ensure voice metrics flow correctly through the data pipeline for reporting and optimization. • Drive improvements in our multi-agent orchestration approach — tool calling patterns, agent handoff logic, and state management across conversation turns. • Advocate for high-quality standards and automated testing strategies for conversational AI systems, including voice-specific test patterns (simulated calls, transcript validation, latency benchmarks). • Identify and resolve voice-specific UX issues: ASR errors on medical terminology, silence detection tuning, barge-in recovery, and end-to-end response latency.