Lead AI Solutions Engineer - New Business

Continental General; Austin (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

Continental General is seeking a Lead AI Solutions Engineer to redefine how insurance platforms use AI. You will lead small, autonomous delivery teams to design and operate AI-driven pipelines with minimal human intervention.

You will architect AWS-based solutions, integrate with vendor SaaS, ensure HIPAA and SOC 2 compliance, and guide toolchains like Claude Code on AWS Bedrock. The role emphasizes ownership, velocity, and auditable security across the full stack.

Qualifications

• Bachelor's degree or equivalent practical experience in CS/IT/Engineering.
• 6+ years in software engineering with AI-driven delivery experience.
• Proven leadership, setting direction and elevating team capability.
• Deep AWS cloud-native architecture and security experience.

Responsibilities

• AI-Native Engineering & Delivery Design, build, and operate AI-driven delivery pipelines with minimal human intervention.
• Build and maintain self-monitoring and self-healing systems with audit traceability for HIPAA/SOC 2.
• Leverage AI agents and workflows across the full software lifecycle including automated test generation and AI-driven code review.
• Evolve AI toolchains and methodologies with governance while maintaining team autonomy.
• Operate within CI/CD pipelines and collaborate with DevOps enablement for production deployments.
• Design AI-native interfaces that are conversational, predictive, and adaptive.
• Architect cloud-native AWS solutions using serverless patterns and Well-Architected practices.
• Ensure secure integration with vendor SaaS and internal systems with data protection.

Skills

AI-driven delivery

Cloud architecture

Security & compliance

CI/CD automation

Effective communication

Education

Bachelor's degree

Tools

Claude Code

AWS Bedrock

Job description

(Full Time, Salary, Exempt)

Position Summary:

The Lead AI Solutions Engineer is a fundamentally different role from traditional software engineering. This role exists within small, domain-aligned delivery teams of 3–5 members where AI is not a supplemental tool, it is the operating model. These teams are designed to deliver at a scale and velocity that far exceeds traditional engineering teams by leveraging AI as a force multiplier across every phase of the delivery lifecycle.

This role carries a dual mandate:

• How you build — Design, operate, and continuously evolve near-autonomous, AI-driven delivery pipelines. From requirements decomposition through deployed, tested, and monitored code, the objective is minimal human intervention with maximum engineering judgment applied at critical decision points.
• What you build — Deliver AI-native solutions that fundamentally re-imagine how users interact with insurance systems. This means extreme flattening of traditional UI layers in favor of intelligent, AI-enabled interfaces. The solutions themselves should be as autonomous as the pipelines that produce them, self-monitoring, self-healing, and requiring minimal human oversight.

These teams operate as domain owners within value stream verticals aligned to core insurance business functions (e.g., Sales Solutions, Customer Solutions, Financial Solutions). Each team owns full-stack delivery including platform, integration, and business-facing systems within their assigned domain. There are no hand-offs to other teams for design, architecture, or implementation. Ownership is real and accountability is complete.

The Lead AI Solutions Engineer operates within a regulated Life, Annuity & Health insurance environment. Autonomous delivery and intelligent solutions must be built within the boundaries of HIPAA, SOC 2, and State Department of Insurance regulations. The aspiration is to push right to the edge of those boundaries, not to avoid them, but to maximize the value of autonomy within the constraints that protect policyholders and the enterprise.

The organization follows principles derived from Team Topologies and Amazon's Single Threaded Owner model. Domain delivery teams are supported by platform teams (Infrastructure/Cloud, IT Operations) who manage organizational commons such as AWS account management, core networking, and edge ingress/egress. Enablement teams (DevOps, QA) provide knowledge resources and maintain separation of duties, with DevOps holding administrative authority over final production deployments. An umbrella security team provides overarching governance. An AI Steering Committee sets enterprise AI strategy and governance guardrails. AI consultants are available to teams for tooling landscape evaluation and guidance.

The primary AI development vehicle is Claude Code via AWS Bedrock, but the toolchain is explicitly non-fixed. The landscape is evolving rapidly, and these teams are expected to evolve with it, evaluating, adopting, and discarding tools as the technology advances. The organization empowers teams to find the right tools for their needs while maintaining alignment with enterprise governance.

Key Responsibilities:

• AI-Native Engineering & Delivery 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.
• Build and 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.
• Intelligent Solution Design & Architecture 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.
• Domain Ownership & Value Stream Delivery Operate as a member of a small, high-accountability delivery team (3–5 members) aligned to a specific business domain within a value stream vertical.
• Own full-stack delivery within the assigned domain including platform, integration, and business/customer-facing solutions and systems.
• Align delivery outcomes to value stream objectives, understanding how technical decisions impact business results in the context of Life, Annuity & Health insurance operations.
• Take genuine ownership of domain systems end-to-end, including architecture decisions, solution design, implementation, and production health.
• Collaboration & Organizational Alignment 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.
• Compliance & Governance Operate within the regulatory frameworks governing Life, Annuity & Health insurance, including HIPAA (protected health information), SOC 2 (security controls), and State Department of Insurance regulations.
• Ensure that AI-driven delivery pipelines and autonomous solutions maintain full audit traceability and comply with enterprise security policies.
• Implement and maintain security best practices including authentication and authorization protocols (OAuth 2.0, OpenID Connect, SAML), API management, data protection, and encryption.
• Understand and respect the regulatory boundaries that constrain autonomous delivery and AI-native solutions, maximizing autonomy within those constraints rather than circumventing them.
• Continuous Evolution Stay at the forefront of AI engineering capabilities, emerging tools, and evolving delivery paradigms.
• Evaluate new technologies, frameworks, and AI capabilities for applicability to the team's domain and delivery model.
• Evolve personal and team delivery processes toward greater autonomy, efficiency, and quality.
• Foster a culture of experimentation and innovation within the team, encouraging the exploration of new approaches while maintaining delivery commitments.

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.
• Deep experience with CI/CD practices and tools, including AI-enhanced pipeline automation.
• 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.