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ICW Group

National commercial insurer with risk management

Director – Applied AI Engineering

Engineering LeadershipPosted on Nov 5
Full-timeSan Diego, CA, USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Technology, Engineering, or a related field is required.
  • At least 10 years of experience in software, data, or machine learning engineering, including at least 5 years in a leadership role, is required.
  • Experience delivering and operating generative or agentic AI solutions in production environments beyond pilots or proofs of concept is required.
  • Experience owning or operating an AI or machine learning platform, including model deployment, versioning, and production monitoring, is required.
  • Experience developing generative AI applications, including retrieval-augmented generation, agentic and multi-agent workflows, and model evaluation methods, is required.
  • Strong working knowledge of generative and agentic AI architectures, foundation model selection, model lifecycle management, and evaluation methods is required.
  • Working knowledge of managed foundation model and agent runtime services, including Amazon Bedrock and Bedrock AgentCore or comparable platforms, and data engineering practices that support retrieval and grounding is required.
  • Strong project management skills to manage complex engineering initiatives with multiple teams, stakeholders, and dependencies are required.
  • Demonstrated ability to mentor and develop engineering team members, with a focus on improving team dynamics and performance, is required.
  • Ability to present technical information to technical and non-technical stakeholders is required.
  • Ability to work effectively where critical dependencies are owned by other teams, through published commitments and shared prioritization, is required.
  • Proven ability to manage cross-functional teams and drive change in complex environments is required.
  • Strong analytical skills to assess business and technical requirements and develop effective solutions are required.
  • The role requires occasional physical activity including reaching, stooping, kneeling, crouching, or crawling, and lifting or moving up to 25 pounds.

Responsibilities

  • Lead the design, development, and production delivery of enterprise generative and agentic AI solutions, including generative AI applications, intelligent document processing, conversational interfaces, and agentic and multi-agent workflows.
  • Own AI Platforms, including managed foundation model services such as Amazon Bedrock, agent runtime and orchestration such as Bedrock AgentCore, and machine learning operations covering model registry, feature engineering, deployment pipelines, model serving, versioning, evaluation, and production monitoring.
  • Operate AI Platforms as a shared enterprise capability, onboarding and supporting engineering, analytics, and data science teams as platform tenants and defining standards and guardrails for their work.
  • Establish and maintain generative and agentic AI engineering standards covering prompt and context management, evaluation frameworks, testing practices, documentation, and release management.
  • Direct the delivery model for generative and agentic AI work, including team structure, capacity planning, and management of commitments to business stakeholders.
  • Partner with data and AI product management to turn the prioritized portfolio into achievable delivery commitments.
  • Oversee production support for generative and agentic AI solutions, ensuring reliability, performance, and issue resolution within established service levels.
  • Maintain capacity for applied research and evaluation of emerging generative and agentic AI capabilities while balancing exploratory work against production delivery commitments.
  • Evaluate emerging generative and agentic AI technologies, foundation models, platforms, and vendors; make build-versus-buy recommendations and recommend adoption when appropriate.
  • Partner with enterprise risk and governance functions to ensure generative, agentic, and machine learning solutions complete required review and approval before production deployment.
  • Collaborate with data services teams to define and secure the data products, semantic models, and pipelines needed to support generative and agentic AI solutions.
  • Partner with cloud and infrastructure engineering teams to define the compute, hosting, security, and scaling requirements on which AI Platforms depend.
  • Partner with financial operations on cost transparency and unit economics for AI Platforms consumption, including token, inference, agent execution, and model cost management.
  • Translate complex cross-functional business and integration needs into actionable development requirements, designs, and plans for engineering teams.
  • Direct the team using key performance indicators and data to inform decision-making.
  • Monitor and evaluate generative and agentic AI engineering performance and make necessary adjustments.
  • Provide strategic and tactical direction to the team, communicate the organizational mission and values, and set standards for performance.
  • Mentor and develop engineering team members, fostering innovation, collaboration, accountability, and professional growth.
  • Establish a collaborative team culture that supports engagement, recognition, retention, continuous development, and high performance.
  • Manage hiring, onboarding, and training for incoming staff; set expectations and develop career paths to build a resilient, skilled team.
  • Directly supervise employees within applied AI engineering and AI Platforms in accordance with company policies and applicable laws.
  • Interview, hire, and train employees; plan, assign, and direct work; conduct performance and salary reviews; reward and discipline employees; address complaints and resolve problems; coach, mentor, and develop team members; create and monitor development plans; set performance expectations and goals; forecast staffing needs and plan for peak times and absences; and enforce department policies and procedures.
  • Supervise through subordinate team leads and manage a blend of employee and contract resources.

Desired Qualifications

  • Experience in insurance or another regulated financial services environment with model governance requirements is preferred.
  • A master's degree in a technical or quantitative discipline is preferred.
  • Cloud and machine learning certifications, including AWS Certified Machine Learning Engineer, AWS Certified Solutions Architect, Microsoft Certified Azure AI Engineer, or other relevant certifications, are preferred.
  • Agile certifications, including Certified Scrum Master, Certified SAFe Practitioner, PMI Agile Certified Practitioner, or other relevant certifications, are preferred.

About the Company

ICW Group

National commercial insurer with risk management

ICW Group provides commercial insurance across the United States, focusing on workers' compensation, catastrophe coverage, and assumed reinsurance. Its products protect businesses from workplace risks and major losses, while its risk-management services help policyholders reduce claim frequency and financial impact. These services emphasize improving workplace safety, employee care, and overall productivity, enabling businesses to manage costs more effectively. To broaden its reach, ICW Group launched ICW Specialty through VerTerra Insurance, offering Excess and Surplus lines to cover niche or higher-risk customers. What sets ICW Group apart is its active risk-management approach and cost-containment services integrated with traditional insurance products, rather than just selling coverage. The company’s goal is to help policyholders minimize claims and costs through proactive risk management while expanding access to specialized insurance markets.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Round Rock, TX
Founded
1972

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