AI Architect

IGH ICW GROUP HOLDINGS, INC.

United States

On-site

USD 106,000 - 189,000

Full time

14 days+

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Job summary

IGH ICW GROUP HOLDINGS, INC. seeks an AI Architect II to lead enterprise AI strategy and hands-on delivery, defining patterns, evaluating AI/ML services, and shaping cloud-native architecture aligned with business goals.

The role requires deep expertise in AWS serverless, MLOps, governance, and guiding engineering teams through risk, performance, and cost optimization while advancing responsible AI practices.

Qualifications

  • Bachelor’s degree in CS, IS, or related field.
  • Minimum 5–7 years with cloud technologies and IT systems.
  • Minimum 2–3 years hands-on with AI/ML technologies including practical application of LLMs or AI/ML services in a cloud environment.

Responsibilities

  • Establish architectural standards, patterns, and reference architectures for AI solutions.
  • Lead the evaluation, selection, and integration of AI/ML services and frameworks.
  • Establish and enforce responsible AI practices including model risk management and data privacy guardrails.
  • Define and oversee MLOps practices for reliable model deployment and lifecycle management.
  • Design enterprise AI patterns including AI gateway architecture and knowledge bases.
  • Design scalable cloud architectures on AWS using serverless technologies.
  • Collaborate with stakeholders to translate business requirements into technical architecture solutions.
  • Lead systems design including microservices, API design, and event-driven patterns across cloud environments.
  • Evaluate emerging AI technologies and provide adoption recommendations.
  • Develop architecture documentation and roadmaps guiding cloud and AI transformation.
  • Provide mentorship on cloud best practices and modern software design principles.

Skills

Cloud architectures
MLOps
AI/ML services
Python scripting
AWS

Education

Bachelor’s degree in Computer Science or related field

Tools

AWS SageMaker
Bedrock
Terraform

Job description

AI Architect II

AI Architect II is a senior technical leadership role working to modernize 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. The role entails making architectural decisions that have real business impact and utilizing expertise to help shape the direction of a rapidly evolving organization.

Essential Duties and 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.
Supervisory Responsibilities

This position has no supervisory responsibility.

Education and Experience

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.

Preferred Certifications
  • 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
Knowledge and Skills
  • 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 OpenWebUI 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.
Physical Requirements

Office environment – no specific or unusual physical or environmental demands and employees are regularly required to sit, walk, stand, talk, and hear.

Work Environment

This position operates in an office environment and requires the frequent use of a computer, telephone, copier, and other standard office equipment.

Compensation

The current range for this position is $105,780.03 – $189,347.93. 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.

In addition to base salary, the company offers a competitive benefits package, including medical, dental, and vision plans; 401(k) retirement plans and company match; bonus potential for all positions; paid time off; and paid holidays throughout the calendar year.

EEO Statement

ICW Group is committed to creating a diverse environment and is proud to be an Equal Opportunity Employer. ICW Group will not discriminate against an applicant or employee on the basis of race, color, religion, national origin, ancestry, sex/gender, age, physical or mental disability, military or veteran status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other characteristic protected by applicable federal, state or local law.

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