Role Description We are seeking an experienced Quantitative Finance Subject Matter Expert to support the development, evaluation, and improvement of advanced Artificial Intelligence (AI) models. This is not a traditional Investment Banking position. Instead, you will apply your real-world expertise to evaluate complex AI-generated financial analyses, validate technical reasoning, identify inaccuracies, and help improve Large Language Models (LLMs) used within the finance industry. We are looking for professionals who are recognized as experts within their field—individuals capable of evaluating financial reasoning with the same rigor expected in investment banking, corporate finance, transaction advisory, and institutional finance environments. Domain Expertise - Quantitative Finance - Financial Engineering - Financial Mathematics - Derivatives - Risk Modeling - Stochastic Calculus - Portfolio Optimization - Model Validation - Quantitative Research What Makes a Strong Candidate - Built pricing models - Validated quantitative models - Published quantitative research Key Responsibilities - Evaluate AI-generated financial analyses for technical accuracy, completeness, and quality of reasoning. - Identify factual inaccuracies, unsupported assumptions, logical inconsistencies, and calculation errors. - Review financial models, valuation methodologies, and investment analyses produced by AI. - Create, review, and refine finance-related prompts, benchmark responses, and evaluation datasets. - Apply detailed annotation guidelines consistently while maintaining exceptional quality standards. - Provide structured, actionable feedback that improves AI model performance. - Collaborate with Project Managers, Quality Assurance teams, and AI Researchers to improve evaluation methodologies. - Maintain productivity and quality expectations while working independently in a remote environment. Required Qualifications - Significant practical experience in Investment Banking, Corporate Finance, or Transaction Advisory. - Strong knowledge of U.S. financial markets and corporate finance principles. - Exceptional analytical and critical thinking skills. - Advanced financial modeling and valuation capabilities. - Excellent written English communication skills. - Ability to independently evaluate complex financial analyses and articulate technical feedback. - Strong attention to detail and commitment to quality. Preferred Qualifications - One or more of the following is highly desirable: - Professional Certifications - CFA (Completed or Candidate) - CPA - MBA (Finance) - Chartered Accountant (CA) Professional Background - Investment Banking - Big Four Transaction Advisory - Valuation Advisory - Private Equity - Venture Capital - Corporate Development - Strategic Finance Financial Platforms - Bloomberg Terminal - Capital IQ - FactSet - Refinitiv - PitchBook AI Experience - Previous experience with any of the following is highly desirable: - AI Model Evaluation - Reinforcement Learning from Human Feedback (RLHF) - Prompt Engineering - AI Annotation - Large Language Model (LLM) Evaluation - AI Quality Assurance - Benchmark Dataset Development U.S. Market Knowledge - Candidates should demonstrate a strong working knowledge of: - SEC Filings - Public Equities - Financial Statements - Valuation Methodologies - Corporate Earnings - Macroeconomic Indicators - Investment Analysis - Capital Markets - Financial Ratios - Portfolio Concepts - Market Trends What Makes a Strong Candidate - Successful candidates are often professionals who have: - Led complex financial analyses or valuation engagements. - Reviewed or approved the work of other finance professionals. - Supported or led high-profile transactions. - Presented recommendations to executive leadership, investment committees, or clients. - Built financial models used in strategic business decisions. - Applied expert judgment to evaluate complex financial scenarios. Trial Gig (Required) As part of the selection process, all shortlisted candidates must successfully complete a Trial Gig designed to evaluate technical finance expertise, analytical reasoning, written communication, attention to detail, and the ability to assess AI-generated financial responses. - Successful completion of the Trial Gig is required before joining the production project. - Candidates who meet the required quality standards will receive an offer to join the project and will be compensated for successfully completing the Trial Gig. - Candidates who do not meet the required quality standards will not move forward on this project and will not receive compensation for the Trial Gig. - Strong candidates who are not selected may remain in our talent network and be considered for future AI evaluation projects that better align with their expertise.

Role Description We are seeking an experienced Quantitative Finance Subject Matter Expert to support the development, evaluation, and improvement of advanced Artificial Intelligence (AI) models. This is not a traditional Investment Banking position. Instead, you will apply your real-world expertise to evaluate complex AI-generated financial analyses, validate technical reasoning, identify inaccuracies, and help improve Large Language Models (LLMs) used within the finance industry. We are looking for professionals who are recognized as experts within their field—individuals capable of evaluating financial reasoning with the same rigor expected in investment banking, corporate finance, transaction advisory, and institutional finance environments. Qualifications - Significant practical experience in Investment Banking, Corporate Finance, or Transaction Advisory. - Strong knowledge of U.S. financial markets and corporate finance principles. - Exceptional analytical and critical thinking skills. - Advanced financial modeling and valuation capabilities. - Excellent written English communication skills. - Ability to independently evaluate complex financial analyses and articulate technical feedback. - Strong attention to detail and commitment to quality. Requirements - Candidates should demonstrate expert-level knowledge in one or more of the following: - Quantitative Finance - Financial Engineering - Financial Mathematics - Derivatives - Risk Modeling - Stochastic Calculus - Portfolio Optimization - Model Validation - Quantitative Research - Previous experience with any of the following is highly desirable: - AI Model Evaluation - Reinforcement Learning from Human Feedback (RLHF) - Prompt Engineering - AI Annotation - Large Language Model (LLM) Evaluation - AI Quality Assurance - Benchmark Dataset Development - U.S. Market Knowledge: Candidates should demonstrate a strong working knowledge of: - SEC Filings - Public Equities - Financial Statements - Valuation Methodologies - Corporate Earnings - Macroeconomic Indicators - Investment Analysis - Capital Markets - Financial Ratios - Portfolio Concepts - Market Trends Benefits - Compensation: United States: $55–$60 USD/hour - Exceptional candidates may be considered for higher compensation based on experience and project requirements. Trial Gig (Required) As part of the selection process, all shortlisted candidates must successfully complete a Trial Gig designed to evaluate technical finance expertise, analytical reasoning, written communication, attention to detail, and the ability to assess AI-generated financial responses. Please note: - Successful completion of the Trial Gig is required before joining the production project. - Candidates who meet the required quality standards will receive an offer to join the project and will be compensated for successfully completing the Trial Gig. - Candidates who do not meet the required quality standards will not move forward on this project and will not receive compensation for the Trial Gig. - Strong candidates who are not selected may remain in our talent network and be considered for future AI evaluation projects that better align with their expertise.

• Lead one of three delivery lanes of AI initiatives at Redcare: Forward deployed AI engineering. • Sitting in between citizen AI supported by AI platform and full-fledged AI products. • You have the opportunity to bring or hire your own team. • Decentral work mode where individual contributors get deployed into the business domain teams. • Need to create space for knowledge sharing, learning and belonging for the ICs in the team. • Support your team members in driving a transformation in the business by active stakeholder management, creating sharing understanding and removing obstacles. • Work 50% hands-on overseeing and driving automation tasks. • Own and drive initiatives of standardization / templates / skills in agentic setup to accelerate onboarding of new business domains.

Role Description We’re building the future of intelligent systems—and we’re looking for an AI and Automation Engineer to help lead the charge. In this role, you’ll design, build, and deploy scalable automation solutions that drive efficiency, reduce manual work, and accelerate innovation across the organization. You’ll work closely with teammates in Information Technology as well as business stakeholders to identify automation opportunities and turn them into reliable, AI-driven workflows. From robotic process automation (RPA) to workflow orchestration and generative AI, your work will have a measurable impact in helping to shape Sarnova’s future. - Design, develop, deploy, and support AI agents using Azure AI Foundry and Microsoft Copilot Studio. - Build conversational, autonomous, and multi-agent solutions using the Foundry SDK, Agent Framework, Responses API, Copilot Studio, and related Microsoft AI technologies. - Design prompt-based and hosted agents, selecting and optimizing models based on business requirements, performance, quality, and cost. - Integrate AI solutions with enterprise data and business systems through APIs, MCP, Power Platform, Dataverse, Dynamics 365, Azure Functions, custom services, and external platforms. - Implement Retrieval-Augmented Generation (RAG) and knowledge-grounding solutions using Azure AI Search, Foundry IQ, and enterprise knowledge sources. - Design and orchestrate multi-agent workflows, Agent-to-Agent (A2A) coordination, routing, and human-in-the-loop processes. - Develop scalable, reusable, secure, and enterprise-ready AI automation solutions. - Monitor, troubleshoot, evaluate, and continuously improve AI solution quality, reliability, safety, and performance. - Create technical documentation, testing assets, operational playbooks, and implementation standards. - Collaborate with business and technical stakeholders to identify, prioritize, and deliver AI-driven solutions that provide measurable business value. - Stay current with emerging AI technologies and advancements across Azure AI Foundry, Copilot Studio, Power Platform, and the Microsoft AI ecosystem. Qualifications - 2+ years of experience in AI development, automation engineering, software development, or a related field. - Hands-on experience designing, developing, deploying, and supporting AI agents using Azure AI Foundry and Microsoft Copilot Studio. - Experience with agent development and orchestration, including prompt-based and hosted agents, Foundry SDK, Agent Framework, Responses API, multi-agent workflows, and agent integrations. - Experience implementing Retrieval-Augmented Generation (RAG) and knowledge-grounding solutions using Azure AI Search, vector search, embeddings, and citation-based responses. - Experience building conversational and autonomous agents in Copilot Studio, including generative answers, knowledge grounding, and workflow automation. - Experience integrating AI solutions with Power Platform, Dataverse, Dynamics 365, APIs, Azure Functions, microservices, and enterprise applications. - Proficiency in Python (preferred), C#, and/or JavaScript/TypeScript, along with modern development tools such as VS Code, Git, Azure DevOps, and Azure CLI. - Knowledge of Model Context Protocol (MCP), custom function tools, external integrations, and API-driven architectures. - Strong understanding of leading LLMs, prompt engineering, context management, conversational memory, model evaluation, and AI solution optimization. - Experience with Azure services including Azure Functions, Azure AI Search, Storage, Key Vault, Microsoft Entra ID, and microservice-based solutions. - Working knowledge of SQL Server, data integration concepts, SharePoint, and Dynamics 365 Finance & Operations and CRM applications. - Familiarity with observability, monitoring, application logging, security, Responsible AI practices, governance, and CI/CD deployment processes. - Experience delivering automation solutions using Power Automate, UiPath, or similar workflow and automation platforms. - Strong analytical, communication, and stakeholder collaboration skills with the ability to translate business requirements into scalable technical solutions. Preferred Qualifications - Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Technology, or a related field; equivalent practical experience will also be considered. - Microsoft certifications related to Azure AI, AI Engineering, Power Platform, Copilot Studio, or Agent Development (e.g., Azure AI Engineer Associate or successor certifications). - Experience in healthcare, regulated, distribution, manufacturing, or other compliance-focused industries with an understanding of security, privacy, and governance requirements. - Experience with one or more of the following advanced Microsoft AI capabilities is highly desirable: - Deploying and managing hosted agents in Azure AI Foundry, including managed runtimes, identity, observability, and enterprise governance. - Designing multi-agent architectures, Agent-to-Agent (A2A) coordination, autonomous workflows, and human-in-the-loop processes. - Developing and maintaining MCP servers, MCP tool catalogs, reusable agent tools, and custom function integrations. - Leveraging Foundry IQ, Azure AI Search, and advanced RAG architectures for enterprise knowledge grounding and retrieval. - Utilizing advanced Azure AI Foundry capabilities such as built-in agent tools, managed memory, evaluation frameworks, observability, guardrails, and governance controls. - Publishing and managing agents across Microsoft Teams, Microsoft 365 Copilot, Dynamics 365, and custom web experiences. - Implementing enterprise AI governance, DLP policies, ALM strategies, environment management, and Responsible AI frameworks. - Experience integrating AI solutions with Microsoft Fabric, Power BI, advanced analytics platforms, or enterprise data ecosystems. - Knowledge of Microsoft Entra Agent ID, managed identities, enterprise authentication, and secure agent access patterns. Physical Requirements - Sit, walk, stand, use hands to manipulate, handle, feel, and control items or equipment. - Reach with hands and arms. - Talk and hear. - See and be able to read, write, and interpret text. - Employee may use computer, phone, copier, and other office equipment in the course of a day. - Occasionally lift and move objects weighing up to 10 pounds. - Employee may be required to travel for business purposes. - When working remotely, ability to secure confidential information. - When working remotely, perform all duties in a professional environment free of noise or anything that would create a negative customer experience. Work Schedule Employee will be required to work a minimum of forty (40) hours of per week or as many hours as it may take to perform above job duties. Schedule may vary based on business demands and will require a combination of office hours as well as work performed after hours and/or weekends at times. Company Description Sarnova is an Equal Opportunity Employer. We offer a competitive salary, commensurate with experience, along with a comprehensive benefits package, including 401(k) Plan. EEO/M/F/Veterans/Disabled. Our mission is to be the best partner for those who save and improve patients’ lives. Excellence in delivering upon our mission is dependent upon having a diverse team that is empowered to bring their full, authentic self to work each day. We strive to create a workplace that reflects the communities we serve, and we are passionate.