Lead AI Solutions Engineer - New Business

Key Responsibilities

• Design, build, and operate AI-driven delivery pipelines that approach near-autonomous execution from requirements decomposition and story generation through code generation, testing, security scanning, and deployment orchestration.
• Maintain self-monitoring and self-healing systems that minimize the need for human intervention in production operations, while maintaining audit traceability required by HIPAA, SOC 2, and State’s Department of Insurance regulatory frameworks.
• Leverage AI agents and agentic workflows across the full software delivery lifecycle, including automated test generation and execution, AI-driven code review, anomaly detection, and auto-remediation.
• Continuously evaluate, adopt, and evolve AI toolchains and development methodologies, maintaining alignment with the AI Steering Committee's governance framework while exercising team-level autonomy in tool selection.
• Operate within CI/CD pipelines and collaborate with DevOps enablement teams for production deployment authority, maintaining clean separation of duties.
• Design and deliver AI-native solutions that replace traditional, UI-heavy interactions with intelligent, AI-enabled interfaces that are conversational, predictive, and adaptive.
• Architect cloud-native solutions on AWS, leveraging managed services and serverless patterns in alignment with the AWS Well-Architected Framework.
• Design secure integration solutions connecting cloud-based applications with vendor SaaS platforms and internal systems, ensuring data security, integrity, and compliance with HIPAA and SOC 2 requirements.
• Apply intelligent automation, predictive analytics, and AI-assisted workflows to improve operational efficiency, customer experience, and business decision-making within insurance domain systems.
• Own all system-specific cloud architectural elements within the team's domain, consuming shared platform services (networking, account management, edge infrastructure) provided by platform teams.
• Collaborate with platform teams (Infrastructure/Cloud, IT Operations) to consume and contribute to shared organizational services and standards.
• Engage with enablement teams (DevOps, QA) as knowledge resources and partners, respecting separation of duties while driving delivery velocity.
• Align with the enterprise AI Steering Committee on governance, strategy, and evolving AI standards.
• Consult with organizational AI consultants on tooling landscape evaluation and emerging capabilities.
• Work with product management, business stakeholders, and vendor representatives to translate business needs into intelligent, AI-native solutions.
• Provide transparent communication on delivery status, risks, and progress to stakeholders and leadership.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. Equivalent practical experience will be considered.
• 6+ years of experience in software engineering, with substantial recent experience in AI-driven development and delivery.
• Demonstrated track record of technical leadership, setting direction, defining patterns, and elevating team capability.
• Expert-level proficiency with AI development tools and agentic workflows, with demonstrated experience building and operating near-autonomous delivery pipelines.
• Deep experience architecting and delivering cloud-native solutions on AWS, including managed services, serverless patterns, and Well-Architected Framework alignment.
• Strong experience designing and delivering AI-native solutions, intelligent interfaces, predictive systems, and autonomous workflows.
• Expert understanding of security protocols and standards (OAuth 2.0, OpenID Connect, SAML, encryption) and their application in AI-driven, regulated environments.
• Strong experience with API design, development, and management (RESTful, SOAP) at an enterprise scale.
• Proficiency across multiple programming languages with the ability to make technology selection decisions based on solution requirements.
• Proven ability to translate regulatory requirements into practical engineering guardrails without sacrificing delivery velocity.
• Exceptional communication skills, able to convey technical direction to the team and translate technical decisions to business stakeholders.