• Recommend and develop comprehensive multi-agent systems and enterprise AI systems for complex applications and products. • Pitch concepts to team leadership and lead construction of prototypes and minimum viable products to validate AI/ML solutions before committing substantial resources. • Assist in designing and implementing the cloud architecture of large multi-faceted AI systems on Kubernetes using platforms like Azure AI Foundry with comprehensive agent governance. • Assist in the design and scaffolding of robust data pipelines that drive large complex AI systems including graph databases, tensor-based fusion, and multi-model retrieval. • Develop specifications for enterprise-wide agent communication standards, tool governance, and evaluation harnesses to deploy AI models at scale. • Develop the code for monitoring models and AI systems including customer evaluation metrics, agent behavior analytics, and comprehensive drift detection that ensures consistent and reliable performance. • Actively participate in a team that exercises principled, agile-like development practices. • Create and maintain thorough documentation that is consistent with team procedures, corporate policies, and expectations including architectural decision records. • Ensure peer review on all assigned work, as well as conduct peer reviews over the work of others as requested. • Guide and mentor junior AI engineers on AI/ML and industry best practices and methodologies and emerging standards like A2A, MCP, and novel reasoning/retrieval techniques. • Keep abreast of new tools and concepts through reading documentation or literature and actively practicing skills development. • Advise team and division leadership on matters such as enterprise AI strategies, AI related technology strategies and roadmaps, AI related infrastructure strategies, and roadmaps. • Meet and collaborate with external stakeholders to conceptualize AI solutions that realize business value while ensuring AI governance adherence, AI best practices, and data quality. • Provide thought leadership to the Premera AI community.

Role Description The Full-Stack AI Engineer (Remote) is responsible for designing, developing, deploying, and maintaining enterprise-grade AI and machine learning (ML) solutions that integrate seamlessly across the company’s technology ecosystem, including Microsoft Copilot Studio, Power Platform, and AWS-based ML environments. This hybrid role bridges AI/ML development, agentic AI orchestration, and MLOps infrastructure, ensuring that models and intelligent agents are secure, scalable, and business-aligned. The position advances the company’s use of AI across all internal and external customer experiences by: - Building and operationalizing AI models and copilots that augment business workflows. - Integrating models into Microsoft Copilot Studio, Power Apps, and Power Automate. - Managing the lifecycle of models deployed through AWS SageMaker, Azure ML, or internal APIs. Qualifications - 5–8 years combined experience in software engineering, ML, and/or MLOps. - Proven success deploying AI/ML models in Microsoft or AWS environments. - Strong proficiency in Python, ML frameworks (Scikit-learn, PyTorch, TensorFlow), and API integration. - Hands-on experience with Microsoft Copilot Studio, Power Automate, and Power Apps development. - Experience deploying AI pipelines in AWS SageMaker or Azure ML. - Familiarity with LLM-based copilots, agent orchestration, and prompt engineering. Requirements - Design, fine-tune, and deploy AI/ML models, including LLMs and retrieval-augmented generation (RAG) pipelines. - Develop and maintain custom Copilots and intelligent agents within Microsoft Copilot Studio that interact with enterprise data and APIs. - Implement Power Platform integrations (Power Apps, Power Automate, Power Virtual Agents) for business-facing AI workflows. - Collaborate with data scientists to transform prototypes into production-grade, secure, and compliant solutions. - Build domain-specific AI skills and agents tailored to insurance and financial processes. - Develop and automate ML pipelines for training, deployment, and monitoring on AWS SageMaker and Azure ML. - Manage CI/CD for AI models and Copilot plugins using MLflow, Airflow, Docker, and Kubernetes. - Implement monitoring for Copilot-based and standalone AI agents, capturing performance, drift, and usage analytics. - Integrate AI governance frameworks ensuring auditability, explainability, and data privacy compliance. - Partner with software engineering and Power Platform teams to embed AI services into core business systems. - Collaborate with IT and Security on Copilot extensions and secure connectors for enterprise data. - Mentor junior AI engineers on cloud AI tools, Copilot integration, and MLOps best practices. Preferred - Experience connecting Copilot agents to proprietary datasets via secure connectors or APIs. - Knowledge of vector databases (Pinecone, FAISS) and RAG architectures. - Familiarity with Azure OpenAI Service, Dataverse, and Microsoft Graph APIs. - Background in financial or insurance domain AI use cases. Education - Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field. Certifications (Preferred) - Microsoft Certified: Azure AI Engineer Associate (AI-102) - Microsoft Certified: Power Platform Solution Architect / Developer Associate - AWS Certified Machine Learning – Specialty - Microsoft Copilot Studio or AI Builder training credentials Physical Requirements Representative of those that must be met by an employee to successfully perform the essential function of the job. Must be able to operate a PC, other relevant office tools/equipment, sit for extended periods, and/or occasionally stand for extended periods, lead training classes and travel. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Compensation Compensation offered for this role is $100,000.00 - $177,150.00 annually and is based on experience and qualifications. Candidates must possess authorization to work in the United States, as it is not our practice to sponsor individuals for work visas. Answer Financial is an equal opportunity employer.

Role Description The AI Solutions Specialist designs, implements, and optimizes AI solutions to solve business problems, collaborating across teams and acting as an SME. Responsibilities include: - Solution Design: - Evaluate and recommend the appropriate Generative AI or Agentic AI tools for each use case. - Translate business and technical requirements into detailed workflows and process diagrams for AI solutions. - Stakeholder Collaboration: - Work with cross-functional teams, including Engineering, Security, Telephony, Sales, Reporting, and Data Science teams to define solution requirements and achieve goals. - Technical Implementation: - Oversee the deployment and management of AI models and tools, ensuring their smooth operation in production environments. - Performance Optimization: - Oversee the evaluation, fine-tuning, and optimization of AI models and infrastructure for optimal performance and scalability. - Data Analysis: - Oversee the analysis and processing of large datasets from AI models and support data-driven decision-making. - Utilize data visualization tools such as PowerBI to report on performance of AI implementations. - Governance: - Coordinate with compliance and data security teams to ensure a framework of processes, policies, and practices consistently guide the reasonable, ethical, and safe development of AI systems. - Tool Administration: - Manage and administer AI-related tools, platforms, and technologies, including cloud services and low-code platforms. - Customer Support: - Provide user enablement and support for AI tools and platforms to promote adoption and efficient use. - Staying Current: - Keep up to date with the latest advancements, technologies, and trends in AI and machine learning. Qualifications - Proficiency in programming languages such as Python, R, or Java. - Strong knowledge of top players such as OpenAI, Gemini, Llama, AWS, and Microsoft Copilot. - Familiarity with cloud platforms such as AWS and Azure for AI deployment and large-scale systems. - Familiarity with agile development tools such as JIRA. - Excellent analytical, logical, and creative problem-solving skills. - Strong communication and stakeholder management skills to collaborate effectively. - Ability to understand customer needs, build business cases, and align AI solutions with business goals. - Understanding of ethical considerations, fairness, and transparency in AI development. Requirements - Compensation offered for this role is $75,100.00 - $130,200.00 annually and is based on experience and qualifications. - Candidates must possess authorization to work in the United States, as it is not our practice to sponsor individuals for work visas. Benefits - Answer Financial is an equal opportunity employer.

• Lead teams in charge of end-to-end development of Conversational AI Agents, from ideation and prompt engineering to production deployment and evaluation • Partner with Product to identify high-impact AI Agent and Chatbot opportunities for workflow automation • Educate the organization on LLM capabilities and trade-offs (latency, cost) to drive superior customer experiences • Oversee data curation, knowledge base construction, and feedback loops essential for successful RAG pipelines • Implement scalable LLMOps frameworks for supporting, evaluating, and securing agent deployments • Research and apply advanced techniques (multi-agent systems, function calling, fine-tuning) to enhance agent capabilities • Align with Engineering and Product leadership on roadmaps to ensure timely delivery of robust production agents • Stay abreast of GenAI trends and integrate new architectures to advance organizational goals • Design and scale a high-velocity AI Engineering organization, focusing on leadership development, organizational culture, and global talent acquisition strategies to sustain rapid growth