Role Description The AI Engineer is accountable for building, testing, and deploying AI-powered solutions that address real-world healthcare challenges within our PACE (Program of All-Inclusive Care for the Elderly) program. This role will leverage enterprise AI models to create intelligent applications such as: - Participant context engines - Retrieval-augmented generation (RAG) pipelines - Agentic workflows The AI Engineer will stay current with the rapidly evolving AI landscape and translate emerging capabilities into production-ready solutions for our business. This role is different because the AI Engineer at WelbeHealth: - Designs and delivers AI-powered solutions that transform how care teams access information, automate complex workflows, and support better participant outcomes through RAG, agentic AI, and enterprise large language models. - Works at the forefront of applied AI innovation, evaluating emerging technologies and translating them into secure, scalable, production-ready applications that enhance operational efficiency, improve decision-making, and support the evolving needs of the PACE model. On the day-to-day, you will: - Design, build, and deploy AI-powered applications using enterprise LLMs (OpenAI, Anthropic Claude, Google Gemini). - Translate PACE business requirements into production-ready AI solutions. - Architect and implement RAG systems that ground AI responses in WelbeHealth's proprietary data. - Own the full development lifecycle for new AI use cases from ideation to production deployment. - Research and build agentic AI workflows using frameworks such as LangGraph, LangChain, or Copilot Studio. - Architect and deploy AI services within private cloud environments (primarily Azure; AWS as needed). - Evaluate and integrate across the frontier model landscape. - Implement AIOps and MLOps best practices. - Continuously evaluate emerging AI tools, techniques, and model releases. Qualifications - Bachelor’s degree required in computer science, AI, computer engineering, or other relevant fields; master’s degree preferred. - Minimum of three (3) years of hands-on experience in AI/ML engineering, applied AI development, or software engineering with a strong AI focus. - Demonstrated experience designing and deploying retrieval-augmented generation pipelines. - Proven ability to build applications on top of commercial LLM APIs (OpenAI, Anthropic, Google). - Advanced proficiency in Python for AI application development, API integration, and data pipeline construction. - Hands-on experience with Azure AI services and Docker-based deployments in secure cloud environments. - Proficiency with Azure DevOps (or equivalent) for building CI/CD pipelines. Benefits - Medical insurance coverage (Medical, Dental, Vision). - Work/life balance - 17 days of personal time off (PTO), 12 holidays observed annually, and 6 sick days. - 401K savings + match. - Comprehensive compensation package including base pay and bonus. - Additional benefits. Compensation Offering $120,164.59 — $158,617.26 USD COVID-19 Vaccination Policy At WelbeHealth, our mission is to unlock the full potential of our vulnerable seniors. In this spirit, please note that we have a vaccination policy for all our employees and proof of vaccination, or a vaccine declination form will be required prior to employment. Our Commitment to Diversity, Equity and Inclusion At WelbeHealth, we embrace and cherish the diversity of our team members, and we're committed to building a culture of inclusion and belonging. We're proud to be an equal opportunity employer.

• Design, build, and implement Generative AI solutions using Large Language Models and modern AI tools. • Develop AI Agent workflows and integrations for business use cases. • Build and integrate APIs using Python. • Work with cloud-based infrastructure and AI services on AWS. • Support the development of scalable, reliable, and secure AI applications. • Collaborate with technical teams and stakeholders to understand requirements and deliver solutions. • Participate in technical discussions, internal interviews, and client-facing conversations when needed. • Contribute to continuous integration, deployment, and engineering best practices. • Work with tools and technologies such as Docker, Kubernetes, Git, CI/CD pipelines, and AWS services. • Troubleshoot, optimize, and improve AI-based solutions as they evolve.

Role Description We’re looking for a Staff Enterprise AI Engineer focused on scaling internal operations across the business through AI-driven systems, agents, and workflow automation. This role designs and delivers secure, production-grade AI solutions that reduce manual work, increase productivity, and improve decision-making across all business functions while maintaining security and privacy. Success is measured by enterprise impact, not tool adoption. Key Responsibilities - AI Systems and Agent Architecture - Design and implement enterprise AI systems using Workato, MCP frameworks, Microsoft 365 Copilot, and Claude. - Build and orchestrate AI agents that automate cross-functional workflows across IT, Security, Finance, HR, Legal, Tech, and GTM. - Develop reusable patterns for agent orchestration, memory, context handling, and human-in-the-loop controls. - Enterprise Automation and Integration - Lead development of end-to-end automated workflows using Workato and related integration platforms. - Connect SaaS systems, data platforms, and internal services into unified AI-powered workflows. - Measurably reduce operational toil by eliminating repetitive manual processes. - AI Governance, Security, and Risk - Embed security, privacy, and compliance controls into AI systems by design. - Ensure alignment with SOC 2, ISO 27001, ISO 42001 and AI governance standards. - Define guardrails for data handling, prompt security, model access, and agent permissions. - Mitigate risks related to prompt injection, data leakage, model misuse, and over-automation. - Platform Enablement and Scale - Build internal AI capabilities that scale across teams, not one-off solutions. - Create reusable templates, SDKs, connectors, and playbooks for AI adoption. - Partner with IT, Security, and Enterprise Apps to operationalize AI at scale. - Productivity and Employee Experience - Leverage Microsoft 365 Copilot and Claude to enhance employee workflows. - Identify high-impact productivity use cases across departments. - Deploy AI assistants that meaningfully reduce time to complete core tasks. - Cross-functional Leadership - Partner with senior stakeholders to identify high-value AI opportunities. - Translate business problems into scalable AI solutions. - Influence roadmap, standards, and adoption strategy across 6sense. Qualifications - 7+ years in enterprise engineering, automation, or IT systems. - Hands-on experience building integrations and workflows using platforms like Workato or similar. - Experience with LLM-based systems including prompt design, agent orchestration, and tool usage. - Strong understanding of SaaS ecosystems and API-driven architectures. - Experience implementing security and compliance controls in cloud-native environments (AWS preferred). - Ability to operate at both deep technical and strategic levels. Preferred Qualifications - Experience with MCP or similar model context and agent frameworks. - Experience with Microsoft 365 Copilot extensibility and Graph API. - Experience with Claude or other enterprise LLM platforms. - Exposure to AI governance frameworks and responsible AI practices. - Background in scaling internal platforms in a high-growth SaaS company. Core Competencies - Systems thinking and platform design. - AI & Automation-first mindset. - Security and risk awareness in AI systems. - Strong technical judgment with bias for action. - Ability to simplify complex workflows through AI. Success Metrics - Reduction in manual workflows and operational overhead. - Measurable productivity gains across key functions. - Adoption and impact of reusable AI solutions across teams. - Compliance and risk posture of AI systems. - Time-to-value for new automation and AI initiatives. Example Impact Areas - AI agents that triage and resolve IT and security tickets. - Automated workflows for finance approvals, HR onboarding, and legal reviews. - Copilot-powered employee assistants integrated with enterprise systems. - Intelligent orchestration of data across SaaS platforms for decision support. Reporting Structure - Reports to: Head of IT and AI Transformation (Part of CISO/CIO org). What Good Looks Like - Ships production-ready AI systems and services, not prototypes. - Builds reusable capabilities, not isolated solutions. - Balances speed with security and governance. - Drives measurable business outcomes, not experimentation for its own sake. Benefits - Full-time employees can take advantage of health coverage, paid parental leave, generous paid time-off and holidays, quarterly self-care days off, and stock options. - Access to equipment and support needed to work and connect with teams, at home or in one of our offices. - Growth mindset culture represented in onboarding and numerous learning and development initiatives including access to LinkedIn Learning platform. - Quarterly wellness education sessions to encourage self-care and personal growth. - Celebration of employee backgrounds through wellness days and ERG-hosted events.

• Sviluppare software in ambito AI, Generative AI e Agentic AI • Collaborare con il team su progetti innovativi e tecnologicamente avanzati • Raccogliere e analizzare requisiti di business • Progettare e implementare soluzioni software scalabili e performanti