GEN AI Engineer/Architect

Iconma Portal•Charlotte, NC

18h

About The Position

Our client, an IT services and consulting company, is seeking a GEN AI Engineer/Architect for its Charlotte, NC location. The role designs and architects end-to-end generative AI solutions that integrate large language models with enterprise data platforms to deliver business capabilities and measurable outcomes. It develops prompt strategies, scalable AWS architectures provisioned with Terraform, data engineering workflows, and solutions using Amazon Bedrock. The position builds Python-based services and pipelines; establishes frameworks to monitor and improve model accuracy, latency, fairness, and robustness; and optimizes inference performance, resource use, and cost. It works with product, engineering, operations, and other stakeholders to turn business needs into practical architectures and roadmaps, while addressing data privacy, security, and compliance. The role also documents architectural patterns and operational runbooks, evaluates emerging tools and approaches, and mentors project teams in prompt engineering, data quality, and model evaluation.

Requirements

Extensive experience in prompt design and delivering generative AI solutions using modern large language models for real-world business challenges.
Strong proficiency in AWS services and Terraform-based infrastructure as code, with experience deploying secure, scalable, and maintainable cloud environments.
Advanced data engineering skills, including data modeling, pipeline development, and performance tuning for AI training and serving workloads.
Practical expertise with Amazon Bedrock and AI model performance management, including monitoring, experimentation, and continuous improvement of model behavior.
Solid Python programming skills for building integrations, APIs, and orchestration layers connecting data systems, AI models, and user applications.
Experience in architect roles in complex enterprise or multinational environments.
Ability to collaborate effectively across distributed teams using hybrid work models.

Responsibilities

Design and architect end-to-end generative AI solutions that integrate large language models with enterprise data platforms.
Develop and refine prompt-design strategies to improve response relevance, reliability, and efficiency across use cases and domains.
Create scalable AWS cloud architectures using Terraform for reproducible provisioning, secure deployments, and robust operations.
Drive data engineering workflows to ingest, transform, and store structured and unstructured data for AI model training, evaluation, and ongoing improvement.
Implement and manage Amazon Bedrock solutions to orchestrate foundation models and integrate them with existing applications.
Establish model performance management frameworks that monitor accuracy, latency, fairness, and robustness, and define metrics and feedback loops for optimization.
Build and maintain Python services, pipelines, and utilities connecting data sources, models, and application layers.
Collaborate with product, engineering, and operations stakeholders to translate business requirements into AI architectures and roadmaps.
Guide design decisions concerning data privacy, security, and compliance in AI solutions.
Optimize LLM inference pipelines and resource utilization to balance performance, cost, and scalability.
Document architectural patterns, solution blueprints, and operational runbooks.
Evaluate emerging generative AI and cloud data engineering tools, frameworks, and patterns and recommend improvements.
Mentor project teams in prompt engineering, data quality management, and model evaluation.