AI Architect (GenAI / MLOps)

HTC Global Services; Charlotte (NC); On-site; USD 140,000 - 190,000; Full time

Job summary

HTC Global Services is seeking an AI Architect to own end-to-end GenAI/ML architectures for enterprise-scale AI initiatives. You will select models, manage data foundations, and govern deployments, collaborating with risk, data, and engineering teams.

The role emphasizes hands-on work with LLMs, MLOps, and cloud services, while guiding executives on feasibility and trade-offs in a fast-paced environment.

Qualifications

• 10+ years in software/data engineering with 4+ years in AI/ML production architectures.
• Hands-on with LLMs/GenAI: prompt engineering, RAG, embeddings, agents.
• Strong Python and ML framework fluency (PyTorch, TensorFlow, scikit-learn).
• Experience with at least one major cloud and its AI services (AWS/Azure/GCP).
• Experience with MLOps tooling (MLflow, Kubeflow, Docker, Kubernetes, CI/CD).
• Data architecture expertise: data lakes/warehouses, streaming, APIs, microservices.
• Knowledge of security, privacy, governance for AI systems.
• Excellent communication to explain trade-offs to leaders.

Responsibilities

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

Skills

Python

ML frameworks

LLMs

GenAI

MLOps

Cloud services

Data architectures

Communication

Education

Advanced degree preferred

Tools

LangChain

LlamaIndex

Docker

Kubernetes

Pinecone/OpenSearch

Job description

Position Overview

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.

Job Description

Job Title: AI Architect (GenAI / MLOps)

What You’ll Do / Key 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

• 10+ 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

What Makes HTC A Great Place To Build Your Future

HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you’ll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You’ll have long-term opportunities to grow your career and develop skills in the latest emerging technologies.

At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks.

Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.

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