Company Description Job Description Role: AI Architect– Insurance (Mandatory) | Azure | API-First Microservices (.NET Program) Duration: Long Term Location: Remote/ EST Experience: 15+ years overall; 4+ years in AI/ML architecture/engineering Role Summary We are building a next-generation insurance platform, including a greenfield P&C Policy Administration System (PAS) with a microservices-based, API-first architecture on Microsoft .NET. As the AI / ML Architect, you will lead the design and delivery of AI-powered capabilities across underwriting, pricing, claims, fraud, and operations. You will define end-to-end AI architecture (data → model → MLOps → serving), ensure secure and compliant AI, and partner closely with product, actuarial, underwriting SMEs, and engineering teams to move from prototypes to production-scale AI. Insurance domain experience is mandatory for this role. Key Responsibilities 1) AI Architecture & Solution Design (End-to-End) - Define the target-state AI/ML architecture for insurance use cases: underwriting decision support, risk scoring, claims triage, fraud detection, pricing optimization, customer/agent assist, and personalization. - Select and guide model approaches: predictive ML, LLMs/GenAI, NLP (and vision models where applicable), with clear tradeoffs and success metrics. - Design API-first AI services that integrate cleanly with microservices (REST/gRPC, event-driven triggers, idempotency, versioning). - Define patterns for feature pipelines, model serving, and governance that work across multiple pods and environments. 2) Model Engineering, MLOps & Deployment (Production Focus) - Lead model development lifecycle: training, evaluation, validation, release, monitoring, and periodic refresh. - Implement MLOps pipelines: automated model testing, monitoring, drift detection, model registries, approval workflows, and rollback strategies. - Define serving patterns (batch/real-time/streaming) and optimize for accuracy, latency, reliability, and cost. 3) Insurance Domain Alignment (Business + Actuarial + Underwriting) - Partner with product owners and translate requirements into AI-enabled components and measurable outcomes. - Ensure AI outputs comply with underwriting guidelines, rating practices, claims workflows, and internal governance. - Design human-in-the-loop controls where needed for regulated decisioning and operational safety. 4) Responsible AI, Security, Compliance & Risk - Establish responsible AI guardrails: explainability, fairness/bias mitigation, audit trails, traceability, and model documentation standards. - Ensure data privacy/security controls across the pipeline: PII handling, access controls, encryption, secrets management, and environment separation. - Collaborate with risk/compliance to meet insurance regulatory expectations for AI systems (governance, reproducibility, reviewability). 5) Platform Integration & Cross-Functional Leadership - Work closely with the Chief Architect, .NET architects, data architect, DevOps, and engineering pods to align AI services to platform standards. - Mentor data scientists/ML engineers; enforce engineering rigor (testing, reliability, monitoring, secure coding). - Drive POCs and technology evaluations, and productize successful capabilities into reusable platform services. 6) AI-Assisted Engineering Enablement (Claude Code, Cursor, MCP) - Use Claude Code and Cursor as first-class development accelerators (code generation, refactoring, test generation, documentation), with strong review and security guardrails. - Standardize patterns for tool usage across teams, including MCP-based workflows/integrations (where applicable), ensuring traceability and quality gates. - Define measurement for productivity and quality improvements (cycle time, rework, defect leakage, release stability). Must-Have Qualifications Insurance Domain (Mandatory) - Proven insurance industry experience is required (P&C preferred): underwriting, rating/pricing, claims triage, fraud, policy servicing, or insurance data/analytics. - Experience designing or integrating ML/AI solutions in insurance decisioning contexts (e.g., risk scoring, pricing, fraud, claims). Technical (Azure-first) - 4+ years hands-on AI/ML engineering and/or architecture experience; overall experience typically 12+ years. - Strong experience with Azure AI ecosystem, including one or more of: - Azure Machine Learning (training, registries, endpoints) - Azure OpenAI / LLM integration patterns - Azure AI Services (language, vision, etc.) - Strong MLOps experience: CI/CD for ML, model registries, monitoring, drift detection, evaluation, and controlled rollouts. - Experience building API-first services and deploying ML systems using Docker and Kubernetes (AKS preferred). Engineering & Collaboration - Strong communication skills: can explain model tradeoffs and risks to non-technical stakeholders and client executives. - Proven ability to lead cross-functional teams in fast-paced environments and ship production outcomes. - Strong P&C insurance experience (Auto/Home/Commercial) and familiarity with PAS workflows. - Experience with event streaming (Kafka/Event Hubs) and real-time inference/feature pipelines. - Experience with responsible AI frameworks and interpretable ML methods in regulated environments. - Azure certifications (Azure AI Engineer / Azure Solutions Architect). Additional Information All your information will be kept confidential according to EEO guidelines.

• Designing, developing, and deploying machine learning models and AI applications that solve complex business problems • Design, build, and maintain AI‑powered search, summarization, and chat applications • Hands‑on experience building or integrating agentic AI systems • Implement information‑retrieval solutions • Develop production‑ready AI applications in Python • Build and tune OpenSearch / Elasticsearch indexes • Evaluate, tune, and refine AI models and system performance through experimentation • Partner with product and business stakeholders to translate requirements into scalable technical solutions

Job Summary The Flight Software & AI Research Intern will support advanced research and development efforts within the Guidance, Navigation, and Controls (GN&C) team, with a primary focus on AI-driven modeling and simulation. This role is designed as a hands-on learning opportunity for graduate students majoring in Computer Science who are interested in applying advanced software engineering and artificial intelligence techniques to aerospace systems, embedded platforms, and high-fidelity simulations. This position supports the development of AI-powered agentic design and execution workflows for 6-DOF modeling and simulation software. The role offers close mentorship from experienced engineers and exposure to real-world aerospace research challenges. This position is based out of Mclaurin Aerospace in Knoxville, TN, with remote work considered for qualified candidates. Why This Role Is Unique This internship offers the opportunity to work at the intersection of AI, flight software, and aerospace research, contributing to real development efforts rather than purely academic exercises. Interns gain meaningful exposure to production-level code, research-grade simulations, and advanced aerospace systems. Responsibilities - Contribute to the design, development, and testing of AI-enabled modeling and simulation software architectures. - Support ongoing development of 6-DOF launch vehicle and spacecraft modeling and simulation software - Prototype system architectures for agentic decision-making assistants - Participate in software verification and validation activities, including unit testing and security demonstration - Create and maintain technical documentation for software architecture, algorithms, interfaces, and test procedures - Collaborate in code reviews, debugging efforts, and flight readiness or system validation activities - Work closely with GN&C engineers and researchers in a fast-paced R&D environment Qualifications - Currently pursuing a Master's degree (preferred) or PhD in Computer Science - This role is intended for true Computer Science majors; other engineering disciplines will be considered only if the candidate demonstrates strong CS depth - Strong programming experience in C/C++ and/or Python - Solid foundation in software engineering principles, algorithms, and data structures - Experience or coursework related to one or more of the following is highly desirable: - Artificial intelligence or machine learning - Using LLMs for decision making applications - Software containerization - Familiarity with Linux-based development environments - Excellent analytical, problem-solving, and debugging skills - Ability to work independently while collaborating effectively with a technical team Additional Requirements & Commitments - Student positions require a minimum commitment of 20 hours per pay period - Some project phases may require additional time commitments; however, schedules are intentionally designed to support and accommodate academic responsibilities - Each intern will work closely with a technical mentor, ensuring alignment between assigned tasks and the student's academic and professional goals - This position is open to US citizen students residing in HUBZone qualified areas only. For more information on HUBZone qualification, see https://maps.certify.sba.gov/hubzone/map.

Role Description We are seeking a highly proactive AI Automation Engineer to help design, develop, and deploy custom AI-powered automation systems. Working closely with the CTO, you will help pioneer AI builds using Claude Code, n8n, and automation frameworks, delivering solutions that improve efficiency and solve real-world operational challenges for clients. This role is client-facing, meaning strong communication skills and the ability to recommend improvements or alternative solutions are essential. The ideal candidate is someone who enjoys problem-solving, building systems from scratch, and finding smarter ways to automate complex workflows. Key Responsibilities - Design and build AI-powered automation systems using Claude Code, n8n, and related platforms. - Develop custom workflows that integrate AI capabilities into business operations. - Collaborate closely with the CTO to prototype and deploy new automation solutions. - Build and maintain scalable AI workflows and automation pipelines. - Troubleshoot, debug, and optimize existing automation builds. - Work directly with clients to understand requirements and recommend the most effective AI solutions. - Proactively identify opportunities to simplify or improve system architecture. - Contribute ideas, improvements, and technical insights to strengthen project outcomes. - Document builds and processes to support long-term system scalability. Qualifications - Proven experience building automation workflows with n8n. - Hands-on experience working with Claude Code or similar AI coding environments. - Strong problem-solving ability and a proactive mindset. - Ability to communicate technical concepts clearly in client-facing conversations. - Comfortable working in a fast-paced startup environment where processes are evolving. - Experience building automation systems that improve operational efficiency. - Strong initiative and willingness to recommend better technical solutions. Requirements - Nice-to-Have Skills: - Programming experience (Python, JavaScript, or similar). - Experience with Make.com or other automation platforms. - Knowledge of Supabase or similar backend infrastructure tools. - Experience with debugging and bug fixing in complex workflows. - Experience designing AI-powered infrastructure or scalable automation systems. - Background in AI integrations or workflow orchestration. Benefits - 💻 Fully Remote: Work from anywhere with international teams. - 🚀 Career Growth: Join companies in SaaS, MarTech, and B2B services. - 🤝 Peer Community: Connect with high-performing sales professionals in our network. - 🧭 Ongoing Support: Receive guidance from Huzzle before and after placement. - 💰 Tailored Compensation: Salaries vary by client and candidate preference — we’ll match you with options that fit your goals.