We're looking for an AI Engineer to join the Fury Team with a deep passion for building next-generation autonomous systems. You’ll work across the stack of perception, reasoning, and control, helping architect and deploy cutting-edge multimodal models that will become the cognitive engine of our robotic platforms. Your work will run on robots in complex, adversarial environments. Expect to move fast, test ideas aggressively, and break new ground as we create the first robotic foundation model for defense. This role may be based remotely for the right candidate. Design, train, and evaluate state-of-the-art VLA models for robotic systems Implement scalable architectures for multimodal model fusion, continual learning, and domain adaptation Develop dynamic memory, communication, and tool use faculties for AI agents Translate foundational research into deployable, real-time perception and decision-making systems Collaborate across engineering, robotics, and mission teams to integrate ML pipelines with onboard autonomy Develop and maintain codebases for training, simulation, and real-world inference Conduct experiments to benchmark performance and robustness in diverse, unstructured environments Track, digest, and incorporate breakthroughs from the latest literature in VLMs, RL, CV, and autonomous agents Support field trials and mission operations to validate model performance under real-world constraints

Osano is an innovative B-Corporation built around a simple belief: privacy is a fundamental right. Since day one, we’ve been focused on giving modern enterprises the ability to innovate quickly, stay competitive, and earn customer trust by respecting data privacy and complying with consent guidelines. Our products help organizations operate confidently in a rapidly evolving regulatory and technological landscape. 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, strict-source-following RAG systems, and 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. 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 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 Develop rigorous evaluation pipelines measuring: Accuracy Citation adherence Latency Reliability Establish metric-driven iteration cycles Continuously refine deployed systems based on measurable outcomes 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 You’re curious, self-directed, and motivated to learn quickly. You’re comfortable navigating ambiguity and creating clarity for others. You’re excited about privacy, responsible AI, and building trustworthy technology. You are willing to relentlessly pursue the best, most responsible ways to leverage AI—without overselling its capabilities or ignoring its limitations. 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 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 We're a welcoming team that's dependable, curious, moves fast, and full of talented people We're a B-corporation with a mission that matters, in a high-growth space with significant potential You'll have access to our training program, well-defined career paths, and a leadership team that values professional development 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 We’re backed by top-tier investors, including Baird Capital, Jump Capital, and LiveOak, and we’re scaling fast with a multi-year runway and ambitious growth plans. We’ve also been recognized as a Great Place to Work for four years running, with 97% of employees saying Osano is a great place to work. Osano is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, marital status, genetic information, disability, veteran status, or any other characteristic protected by applicable law. Osano is a leading data privacy platform that helps organizations quickly and confidently comply with laws like GDPR, CCPA, and other global privacy regulations. From consent management to vendor risk monitoring, Osano makes complex privacy tasks refreshingly simple, so companies can focus on what they do best, while we handle the rest. We’re backed by top-tier investors including Baird Capital, Jump Capital, and LiveOak, and we’re scaling fast with a multi-year runway and ambitious growth plans. We’ve also been recognized as a Great Place to Work for four years running, with 97% of employees saying Osano is a great place to work. As we grow, we're looking for individuals who lean into modern technologies and smarter systems to drive efficiency, clarity, and speed; both in our product and in how we operate. If you're excited by the idea of helping build a high-growth, privacy-first company that embraces thoughtful automation, emerging tech, and intentional collaboration, we’d love to hear from you.

• Architect our core AI assistant: Lead the technical development of an agent that helps construction professionals process, improve, and validate complex construction documents. • Engineer robust agentic workflows: Own tool use, complex RAG pipelines, guardrails, and sub-agent orchestration. • Master context and memory: Solve state-management challenges to ensure coherent, long multi-turn interactions. • Own the feedback loop: Implement online and offline evaluation frameworks to balance latency, cost, and quality. • Drive product impact: Work with Product and Engineering to turn ambiguous business problems into concrete technical solutions. • Production-grade engineering: Write clean Python code and establish observability so agents are reliable in production. • Explore future horizons: Identify opportunities to expand capabilities, for example with multimodal inputs like visual plans.

• Design and deploy a locally hosted LLM-powered agent for autonomous payment failure analysis • Build internal LLM infrastructure with no external API dependency for core workflows • Develop structured pipelines for root cause identification across transaction failures • Automate Level 1 incident investigations • Generate standardized root cause analysis (RCA) reports • Optimize model performance to reduce Mean Time to Resolution (MTTR) • Develop scalable training and inference pipelines • Create reusable model components adopted across multiple use cases • Reduce time-to-deploy new AI applications • Decrease reliance on external AI APIs through internal model development • Implement monitoring systems for latency, drift, and model performance • Deploy at least two additional AI use cases (e.g., chatbot, automated reporting, issue clustering) • Ensure ≥99.9% production uptime • Maintain inference latency within defined thresholds • Establish retraining cadence and continuous performance evaluation • Deliver measurable efficiency improvements in operational workflows • Implement version-controlled datasets and model versioning • Define evaluation benchmarks (precision, recall, accuracy thresholds) • Implement automated drift detection • Document model architecture and training processes • Ensure zero preventable production-critical failures due to model design • Ensure personal information of customers, employees, and other individuals processed and protected in line with applicable data privacy policies.