Job Title: AI Architect
Location: Charlotte, NC (Hybrid)
Duration: 1 year
Experience Level: Lead (8-10 years)
Job Summary
We are seeking a highly skilled and hands-on AI Architect to lead the design and implementation of next-generation enterprise AI platforms powered by Large Language Models (LLMs) and advanced agentic architectures. The ideal candidate will possess deep expertise in scalable AI system design, AWS-native AI services, multi-agent orchestration, LLM evaluation frameworks, guardrails, and performance optimization.
This role requires a unique combination of advanced technical leadership, architectural vision, and hands-on engineering expertise to build secure, scalable, production-grade AI solutions that support complex enterprise workflows.
Key Responsibilities
Enterprise AI & LLM Architecture
(8+ years overall experience, including 4+ years in AI/ML architecture)
Architect and deliver enterprise-scale AI platforms leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), fine-tuning strategies, and advanced agentic AI architectures.
Design and implement multi-agent systems capable of:
Tool orchestration
Autonomous planning and reasoning
Context and memory management
Distributed workflow execution
Define scalable AI architecture patterns supporting high availability, security, observability, and enterprise governance.
Lead the integration of AI systems into enterprise applications, APIs, and cloud-native ecosystems.
LLM Guardrails & Responsible AI
(1+ years of hands-on experience)
Design and implement robust guardrails for enterprise LLM applications, including:
Content filtering
Prompt injection mitigation
Hallucination reduction
Policy enforcement and compliance controls
Implement responsible AI practices using:
Safety frameworks
Human-in-the-loop validation
Governance and audit mechanisms
Ensure ethical, compliant, reliable, and secure AI usage across enterprise environments.
LLM Cost Optimization & Performance Engineering
(1+ years of relevant experience)
Optimize LLM workloads for:
Cost efficiency
Low latency
High throughput
Operational scalability
Implement:
Model selection strategies
Prompt optimization techniques
Token usage optimization
Response caching and batching mechanisms
Design scalable inference architectures and usage monitoring frameworks to balance performance with operational cost.
Evaluation Frameworks & Model Quality Engineering (Evals)
(1+ years of hands-on experience)
Develop and operationalize comprehensive evaluation frameworks for LLM applications, including:
Automated benchmarking
Prompt evaluation
Response scoring
Regression testing
Implement both offline and online evaluation methodologies, including:
Human evaluation pipelines
A/B testing frameworks
Continuous feedback loops
Continuously improve model quality, reliability, and production performance using measurable evaluation metrics.
AWS Bedrock & Agentic Frameworks
(2+ years of hands-on experience)
Hands-on expertise with Amazon Bedrock, including:
Foundation model evaluation
Prompt engineering
AI orchestration
Model lifecycle management
Experience with AgentCore or equivalent agentic frameworks for building:
Stateful AI agents
Tool-augmented agents
Memory-enabled agent systems
Controlled execution workflows
Design composable AI services using cloud-native orchestration patterns.
Advanced Python & API Engineering
(6+ years of experience)
Expert-level proficiency in Python and modern AI/ML ecosystems, including:
PyTorch
TensorFlow
Hugging Face
LangChain or equivalent frameworks
Build scalable, production-grade APIs using FastAPI, including:
Async processing
AI model inference optimization
High-performance microservices architecture
Develop reusable AI service components and distributed API integrations.
CI/CD and MLOps for AI Systems
(5+ years of experience)
Design and implement robust CI/CD pipelines for AI and ML applications, including:
Automated model testing
Validation workflows
Reproducibility controls
Staged deployments and rollbacks
Implement MLOps best practices using:
Model versioning
Feature stores
Continuous monitoring
Automated retraining workflows
Experience with tools and platforms such as:
GitHub Actions
Jenkins
AWS CodePipeline
Terraform
CloudFormation
AWS Cloud Architecture
(2+ years of experience)
Design secure and scalable AWS cloud architectures for AI workloads.
Strong understanding of Amazon VPC architecture, including:
Subnetting strategies
Private networking
Security segmentation
High-availability design
Hands-on experience with:
AWS Lambda
API Gateway
SQS
Step Functions
Event-driven serverless architectures
Build scalable inference pipelines and cloud-native integrations across AWS services.
Distributed Team Leadership & Global Delivery
(5+ years of leadership experience)
Lead distributed AI engineering and platform development teams across multiple time zones.
Drive high productivity, technical alignment, and delivery excellence across globally distributed teams.
Implement agile delivery methodologies and scalable engineering processes.
Collaborate cross-functionally with architecture, engineering, product, security, and operations teams.
Required Qualifications
8+ years of overall software engineering experience
4+ years of AI/ML architecture experience
Deep expertise in LLM ecosystems, RAG pipelines, and agentic AI architectures
Strong hands-on experience with AWS-native AI services and cloud platforms
Expertise in Python-based AI application development
Experience building scalable enterprise AI systems in production environments
Strong understanding of AI governance, responsible AI, and evaluation methodologies
Excellent communication, architectural, and leadership skills
Preferred Qualifications
Experience working with enterprise AI governance frameworks
Knowledge of vector databases and semantic search architectures
Familiarity with distributed systems and event-driven microservices
Experience supporting globally distributed engineering organizations
AWS certifications or AI/ML specialization certifications preferred
Top 5 Must-Have Skills
1. AI & LLM Architect
2. LLM Guardrails & Responsible AI
3. Advanced Python & API Engineering
4. api
5. microservices
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