PURPOSE OF THE JOBThe Director of Applied AI Engineering is a senior leader responsible for the delivery and operation of generative and agentic AI solutions across the enterprise. This role leads a team of engineers who design, build, deploy, and support generative and agentic AI capabilities that address business needs in underwriting, claims, distribution, finance, and corporate operations. The Director owns AI Platforms, the shared enterprise capability through which these solutions reach and remain in production, comprising managed foundation model services, agent runtime and orchestration, and machine learning operations. The Director sets engineering standards for generative and agentic AI development and establishes the operating model by which this work is delivered and supported. The Director collaborates closely with data services, cloud and infrastructure engineering, product management, and enterprise risk and governance functions to ensure solutions are well-founded, responsibly deployed, and sustainable in production.
ESSENTIAL DUTIES AND RESPONSIBILITIES - Leads the design, development, and production delivery of generative and agentic AI solutions across the enterprise, including generative AI applications, intelligent document processing, conversational interfaces, and agentic and multi-agent workflows.
- Owns AI Platforms, including managed foundation model services (Amazon Bedrock), agent runtime and orchestration (Bedrock AgentCore), and machine learning operations - model registry, feature engineering, deployment pipelines, model serving, versioning, evaluation, and production monitoring.
- Operates AI Platforms as a shared enterprise capability, onboarding and supporting engineering, analytics, and data science teams as platform tenants and defining the standards and guardrails under which they build.
- Establishes and maintains engineering standards for generative and agentic AI development, including prompt and context management, evaluation frameworks, testing practices, documentation, and release management.
- Directs the delivery model for generative and agentic AI work, including team structure, capacity planning, and management of commitments to business stakeholders.
- Partners with data and AI product management, who own intake and prioritization, to convert the prioritized portfolio into achievable delivery commitments.
- Oversees production support for generative and agentic AI solutions, ensuring reliability, performance, and issue resolution within established service levels.
- Maintains capacity for applied research and evaluation of emerging generative and agentic AI capabilities, balancing exploratory work against production delivery commitments.
- Evaluates emerging generative and agentic AI technologies, foundation models, platforms, and vendors; makes build-versus-buy recommendations and recommends adoption when appropriate.
- Partners with enterprise risk and governance functions to ensure generative, agentic, and machine learning solutions complete required review and approval prior to production deployment.
- Collaborates with data services teams to define and secure the data products, semantic models, and pipelines required to support generative and agentic AI solutions.
- Partners with cloud and infrastructure engineering teams, who own on-premise and cloud hosting, to define the compute, hosting, security, and scaling requirements on which AI Platforms depends.
- Partners with financial operations on cost transparency and unit economics for AI Platforms consumption, including token, inference, agent execution, and model cost management.
- Translates complex, cross-functional business and integration needs into actionable development requirements, designs, and plans for engineering teams.
- Directs the team utilizing KPIs and data to inform decision making.
- Monitors and evaluates the performance of generative and agentic AI engineering activities and makes necessary adjustments.
- Provides strategic and tactical direction to the team, communicating the organizational mission and values, and setting standards for performance excellence.
- Mentors and develops engineering team members, fostering a culture of innovation, collaboration, accountability, and professional growth.
- Establishes a collaborative team culture ensuring high engagement, recognition, and retention of team members. Ensures leadership practices promote continuous development and high performance.
- Manages hiring, onboarding, and training for incoming staff, setting clear expectations and developing career paths to build a resilient, skilled team.
SUPERVISORY RESPONSIBILITIES Directly supervises employees within the applied AI engineering and AI Platforms teams and carries out supervisory responsibilities in accordance with company policies and applicable laws. These responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; conducting performance and salary reviews; rewarding and disciplining employees; addressing complaints and resolving problems; coaching, mentoring, and developing team members to further their skills and knowledge; creating and monitoring development plans; setting performance expectations and goals; forecasting staffing needs and planning for peak times and absences; enforcing department policies and procedures. Supervises through subordinate team leads and manages a blend of employee and contract resources.
EDUCATION AND EXPERIENCE - Bachelor's degree required in Computer Science, Information Technology, Engineering, or related field.
- Minimum 10 years of experience in software, data, or machine learning engineering, with at least 5 years in a leadership role required.
- Experience delivering and operating generative or agentic AI solutions in production environments, beyond pilots or proofs of concept, required.
- Experience owning or operating an AI or machine learning platform, including model deployment, versioning, and production monitoring, required.
- Experience with generative AI application development, including retrieval-augmented generation, agentic and multi-agent workflows, and model evaluation methods, required.
- Experience in insurance or another regulated financial services environment with model governance requirements preferred.
- Master's degree in a technical or quantitative discipline preferred.
LICENSES AND CERTIFICATIONS - Cloud and machine learning certifications including but not limited to AWS Certified Machine Learning Engineer, AWS Certified Solutions Architect, Microsoft Certified Azure AI Engineer, or other relevant certifications preferred.
- Agile certifications including but not limited to Certified Scrum Master (CSM), Certified SAFe practitioner, PMI Agile Certified Practitioner (PMI-ACP), or other relevant certifications preferred.
KNOWLEDGE AND SKILLS - Strong working knowledge of generative and agentic AI architectures, foundation model selection, model lifecycle management, and evaluation methods.
- Working knowledge of managed foundation model and agent runtime services, including Amazon Bedrock and Bedrock AgentCore or comparable platforms, and of the data engineering practices that support retrieval and grounding.
- Strong project management skills, with the ability to manage complex engineering initiatives with multiple teams, stakeholders, and dependencies.
- Demonstrated ability to mentor and develop engineering team members, with a focus on improving team dynamics and performance.
- Excellent communication and stakeholder management skills, with the ability to present technical information to both technical and non-technical stakeholders.
- Ability to operate effectively where critical dependencies are owned by other teams, working through published commitments and shared prioritization.
- Proven ability to manage cross-functional teams and drive change in complex environments.
- Strong analytical skills to assess business and technical requirements and develop effective solutions.
PHYSICAL DEMANDS The employee may need to sit in front of a computer for a period of time. While performing the duties of this job, the employee may occasionally need to reach, stoop, kneel, crouch, or crawl. The employee may need to lift and/or move up to 25 pounds.
WORK ENVIRONMENT This position operates in an office environment and requires the frequent use of a computer, telephone, copier, and other standard office equipment.
This description is a general statement of essential job functions and responsibilities. It does not exclude other duties as assigned.
The current range for this position is
$160,745.90 - $287,738.43
This range is exclusive of fringe benefits and potential bonuses. If hired at ICW Group, your final base salary compensation will be determined by factors unique to each candidate, including experience, education and the location of the role and considers employees performing substantially similar work.
WHY JOIN ICW GROUP?- Challenging work and the ability to make a difference
- You will have a voice and feel a sense of belonging
- We offer a competitive benefits package, with generous medical, dental, and vision plans as well as 401K retirement plans and company match
- Bonus potential for all positions
- Paid Time Off
- Paid holidays throughout the calendar year
- Want to continue learning? We'll support you 100%
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