AI Architect (GenAI/MLOps)

Requirements:

• 10+ years of experience in software or data engineering, including at least 4 years architecting production AI/ML solutions.
• Hands-on experience with LLMs and generative AI, including prompt engineering, RAG, embeddings, and agent frameworks such as LangChain or LlamaIndex.
• Strong Python skills and proficiency with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Deep experience with at least one major cloud platform—AWS, Azure, or GCP—and its AI services, such as SageMaker, Bedrock, Azure OpenAI, or Vertex AI.
• Experience with MLOps tools and practices, including MLflow, Kubeflow, Docker, Kubernetes, and CI/CD.
• Strong foundation in data architecture, including data lakes or warehouses, streaming, APIs, and microservices.
• Knowledge of AI security, privacy, and governance.
• Excellent communication skills, including the ability to explain technical trade-offs to nontechnical leaders.
• Preferred: Experience in banking, insurance, or asset or wealth management, including familiarity with regulatory expectations such as SR 11-7 model risk.
• Preferred: Experience with vector databases such as Pinecone, pgvector, or OpenSearch, and with fine-tuning or evaluation frameworks.
• Preferred: Cloud or architecture certifications, such as AWS ML Specialty, Azure AI Engineer, or TOGAF.
• Preferred: A masters or PhD in Computer Science, Data Science, or a related field.

Responsibilities:

• Design end-to-end AI/ML and generative AI architectures, including RAG, agents, fine-tuning, and model serving, integrated with existing enterprise platforms.
• Assess and select LLMs, vector databases, orchestration frameworks, and MLOps tools.
• Establish reusable reference architectures, design patterns, and standards across teams.
• Work with data engineering teams on pipelines, feature stores, and data quality for AI workloads.
• Incorporate responsible AI practices, including model risk management, explainability, bias testing, audit trails, and regulatory compliance.
• Set up MLOps and LLMOps practices for CI/CD, evaluation, observability, drift detection, and cost management.
• Lead proofs of concept and pilots through to production deployment.
• Advise stakeholders and executives on AI strategy, feasibility, and trade-offs.
• Mentor engineers and data scientists and lead architecture reviews.

Technologies:

• AI
• AWS
• OpenSearch
• Architect
• Azure
• CI/CD
• Cloud
• Docker
• Fine-tuning
• GCP
• Kubeflow
• Kubernetes
• MLflow
• MLOps
• Model Serving
• PyTorch
• Python
• RAG
• Security
• TOGAF
• TensorFlow
• microservices

More

We are hiring an AI Architect (GenAI / MLOps) to lead enterprise AI and generative AI architecture from data foundations and model selection through deployment, governance, and monitoring. At HTC Global Services, you will collaborate with experts, work alongside clients, and contribute to high-performing teams. We offer long-term career growth and opportunities to develop skills in emerging technologies. Our benefits may include medical, dental, and vision coverage, paid time off and holidays, 401(k) matching, life and disability insurance, professional development, wellness programs, and other perks. We are committed to an inclusive, diverse workplace free from discrimination and harassment, where employees are treated with dignity and respect.

last updated 43 week of 2026