AI Architect

ICW Group • San Diego, CA

3d • $105,780 - $189,348 • Onsite

About The Position

Are you looking to make an impactful difference in your work, yourself, and your community? Why settle for just a job when you can land a career? At ICW Group, we are hiring team members who are ready to use their skills, curiosity, and drive to be part of our journey as we strive to transform the insurance carrier space. We're proud to be in business for over 50 years, and its change agents like yourself that will help us continue to deliver our mission to create the best insurance experience possible. Headquartered in San Diego with regional offices located throughout the United States, ICW Group has been named for ten consecutive years as a Top 50 performing P&C organization offering the stability of a large, profitable and growing company combined with a focus on all things people. It's our team members who make us an employer of choice and the vibrant company we are today. We strive to make both our internal and external communities better everyday! Learn more about why you want to be here! PURPOSE OF THE JOB The AI Architect II is a senior technical leadership role working to modernizing the company’s technology platform. This position will provide both thought and technical leadership, influencing cloud and AI strategy while working hands-on to deliver solutions that matter. This role will make architectural decisions that have real business impact and utilize expertise to help shape the direction of a rapidly evolving organization.

Requirements

• Bachelor's degree required in Computer Science, Information Systems, or related field.
• Minimum 5–7 years with cloud technologies and IT systems, with demonstrated expertise in enterprise-scale solution design and delivery.
• Minimum 2–3 years hands-on with AI/ML technologies including practical application of LLMs, agentic frameworks, or AI/ML services in a cloud environment.
• Strong understanding of AI concepts including LLMs, AI agents, agentic frameworks, Model Context Protocol (MCP), Agent-to-Agent (A2A) communication, and prompt engineering.
• Hands-on experience with AWS AI/ML services: Amazon Bedrock, SageMaker, Kendra, and Amazon Q Business for building and deploying intelligent applications.
• Familiarity with LLM fine-tuning, embedding models, vector stores, and chunking strategies for RAG pipelines.
• Experience with AI orchestration frameworks such as LangChain, LangGraph, and AWS Strands Agents for multi-step agentic workflows.
• Knowledge of frontier model evaluation, benchmarking methodologies, and model selection criteria for responsible and cost-effective AI adoption.
• Familiarity with open-source AI tooling such as Open WebUI and LiteLLM for unified LLM API gateway and proxy management.
• Understanding of responsible AI principles including bias detection, model risk management, content filtering, PII handling, and data residency; Amazon Bedrock Guardrails experience preferred.
• Familiarity with MLOps tooling including SageMaker Pipelines or MLflow for model versioning, experiment tracking, and drift detection.
• Knowledge of LLM function calling, structured output patterns, and tool integration techniques for reliable agentic systems.
• Familiarity with multimodal AI use cases including document understanding, image analysis, and audio processing.
• Understanding of AI cost and performance optimization: token management, prompt caching, model quantization, and right-sizing for inference workloads.
• Deep knowledge of AWS cloud services with emphasis on serverless architectures and design patterns.
• Proficiency in Linux and Windows system administration including networking, storage, security, and scripting.
• Proficiency in Python for scripting, automation, and cloud-native application development.
• Hands-on experience with Snowflake, AWS Aurora (PostgreSQL), DynamoDB, Glue, Redshift, Athena, S3-based data lakes, and data pipeline design.
• Experience with infrastructure-as-code tools: AWS CDK, CloudFormation, or Terraform for automated, repeatable cloud deployments.
• Knowledge of enterprise integration patterns, RESTful API design, event-driven architecture, and microservices design principles.
• Familiarity with DevSecOps practices including CI/CD pipelines, automated testing, container orchestration (ECS, EKS), and security-by-design.
• Understanding of cloud cost management, FinOps principles, and architectural trade-off analysis.
• Experience with observability and monitoring tools: Amazon CloudWatch, AWS X-Ray, and third-party APM solutions.
• Strong communication skills with the ability to present complex technical concepts to both technical and non-technical audiences, including executive leadership.

Nice To Haves

• TOGAF, Zachman Framework, FEAF
• Solutions Architect Associate, Solutions Architect Professional, Machine Learning – Specialty, Data Engineer
• SnowPro Core, SnowPro Advanced Architect
• AI/ML, Data Engineering, DevOps, Security

Responsibilities

• Establish architectural standards, patterns, and reference architectures for AI solutions — covering RAG pipelines, agentic workflows, model serving, and AI gateway design.
• Lead the evaluation, selection, and integration of AI/ML services and frameworks including LLMs, AI agents, and multi-agent systems using protocols such as MCP and A2A.
• Establish and enforce responsible AI practices including model risk management, content filtering, and data privacy guardrails across AI initiatives.
• Define and oversee MLOps practices to ensure reliable model deployment, monitoring, and lifecycle management across the enterprise.
• Design enterprise AI patterns including AI gateway architecture, knowledge bases, and integration of AI capabilities into existing business systems and workflows.
• Design and implement scalable cloud architectures on AWS, leveraging serverless technologies and design patterns.
• Define and enforce cloud architecture standards, patterns, and guardrails across development teams to ensure consistency, security, and cost optimization.
• Collaborate with business and technology stakeholders to translate business requirements into technical architecture solutions aligned with enterprise strategy.
• Lead systems design efforts including microservices architecture, API design, event-driven systems, and integration patterns across cloud-native and hybrid environments.
• Evaluate emerging AI technologies and provide recommendations on adoption strategies, including generative AI, agentic workflows, and intelligent automation.
• Develop and maintain architecture documentation, reference architectures, and technology roadmaps guiding the organization's cloud and AI transformation.
• Provide technical mentorship and guidance to engineering teams on cloud best practices, AI implementation patterns, and modern software design principles.
• Conduct architecture reviews, risk assessments, and proof-of-concept initiatives to validate technology decisions and drive innovation.
• Lead application rationalization initiatives to assess, consolidate, and modernize the application portfolio, reducing technical debt and aligning technology investments with business priorities.

Benefits

• 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%

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level