AI Architect (GenAI / MLOps)

Robotics Technologies; Charlotte (NC); On-site; USD 90,000 - 128,000; Full time

Job summary

Robotics Technologies LLC is seeking an AI Architect to own enterprise GenAI and MLOps architectures in Charlotte, NC. You will design end-to-end AI solutions, from data foundations to model deployment, governance, and monitoring, collaborating with business and risk teams.

You should have 6+ years in software/data engineering and 4+ years building production AI/ML systems, strong Python, cloud AI services, and MLOps tooling. Excellent communicator with leadership experience is essential.

Qualifications

• 6+ years in software or data engineering, with 4+ years architecting AI/ML in production.
• Hands-on with LLMs and GenAI: prompt engineering, RAG, embeddings, agent frameworks (LangChain, LlamaIndex).
• Strong Python skills and ML frameworks (PyTorch, TensorFlow, scikit-learn).
• Deep experience with at least one major cloud (AWS, Azure, or GCP) and its AI services (SageMaker, Bedrock, Azure OpenAI, Vertex AI).
• Experience with MLOps tooling (MLflow, Kubeflow, Docker, Kubernetes, CI/CD).
• Solid grounding in data architecture: data lakes/warehouses, streaming, APIs, and microservices.
• Knowledge of security, privacy, and governance for AI systems
• Excellent communication, with the ability to explain technical trade-offs to non-technical leaders

Responsibilities

• Design end-to-end AI/ML and GenAI architectures integrating with enterprise platforms.
• Evaluate and select LLMs, vector databases, orchestration frameworks, and MLOps tooling.
• Define reference architectures, patterns, and standards for reuse across teams.
• Partner with data engineering on pipelines, feature stores, and data quality for AI workloads.
• Build in responsible AI: model risk management, explainability, bias testing, audit trails, and regulatory compliance.
• Establish MLOps/LLMOps practices covering CI/CD, evaluation, observability, drift detection, and cost control.
• Lead proofs of concept and pilots, and move them to production.
• Advise stakeholders and executives on AI strategy, feasibility, and trade-offs.
• Mentor engineers and data scientists, and run architecture reviews.

Skills

AI/ML architecture

Python

Cloud platforms

MLOps

LangChain/LlamaIndex

Data engineering

Communication

Education

Master's degree in CS/DS

PhD in CS/DS

Tools

LangChain

LlamaIndex

PyTorch

TensorFlow

SageMaker

Kubeflow

Docker

Kubernetes

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title:AI Architect (GenAI / MLOps)
Location:Charlotte, NC
Duration: 8 Months + Extension
Bill Rate: $79/hour (C2C)
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H-4-EAD, Other

Job Description

Turning promising AI ideas into production systems that are secure, compliant, and built to scale is the hard part of enterprise AI. This role sits at the center of that work. You’ll own the architecture for enterprise AI and GenAI solutions end to end, from data foundations and model selection through deployment, governance, and monitoring. You’ll work closely with business, data, engineering, and risk teams, and you’ll advise executives on what’s feasible, what’s worth it, and what the trade-offs are.

Responsibilities

• Design end-to-end AI/ML and GenAI architectures (RAG, agents, fine-tuning, model serving) that integrate with existing enterprise platforms
• Evaluate and select LLMs, vector databases, orchestration frameworks, and MLOps tooling
• Define reference architectures, patterns, and standards for reuse across teams
• Partner with data engineering on pipelines, feature stores, and data quality for AI workloads
• Build in responsible AI: model risk management, explainability, bias testing, audit trails, and regulatory compliance
• Establish MLOps/LLMOps practices covering CI/CD, evaluation, observability, drift detection, and cost control
• Lead proofs of concept and pilots, and move them to production
• Advise stakeholders and executives on AI strategy, feasibility, and trade-offs
• Mentor engineers and data scientists, and run architecture reviews

Required Qualifications

• 6+ years in software or data engineering, with 4+ years architecting AI/ML solutions in production
• Hands-on experience with LLMs and GenAI: prompt engineering, RAG, embeddings, and agent frameworks (e.g., LangChain, LlamaIndex)
• Strong Python skills and fluency in ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Deep experience with at least one major cloud (AWS, Azure, or GCP) and its AI services (e.g., SageMaker, Bedrock, Azure OpenAI, Vertex AI)
• Experience with MLOps tooling (MLflow, Kubeflow, Docker, Kubernetes, CI/CD)
• Solid grounding in data architecture: data lakes/warehouses, streaming, APIs, and microservices
• Knowledge of security, privacy, and governance for AI systems
• Excellent communication, with the ability to explain technical trade-offs to non-technical leaders

Preferred Qualifications

• Experience in banking, insurance, or asset/wealth management, including regulatory expectations (e.g., SR 11-7 model risk)
• Experience with vector databases (Pinecone, pgvector, OpenSearch) and fine-tuning or evaluation frameworks
• Cloud or architecture certifications (e.g., AWS ML Specialty, Azure AI Engineer, TOGAF)
• Master's or PhD in Computer Science, Data Science, or a related field

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.