AI Architect (GenAI / MLOps)

Job Description

Job Title: AI Architect (GenAI / MLOps)

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.

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 platformsEvaluate and select LLMs, vector databases, orchestration frameworks, and MLOps toolingDefine reference architectures, patterns, and standards for reuse across teamsPartner with data engineering on pipelines, feature stores, and data quality for AI workloadsBuild in responsible AI: model risk management, explainability, bias testing, audit trails, and regulatory complianceEstablish MLOps/LLMOps practices covering CI/CD, evaluation, observability, drift detection, and cost controlLead proofs of concept and pilots, and move them to productionAdvise stakeholders and executives on AI strategy, feasibility, and trade-offsMentor 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 productionHands-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 microservicesKnowledge of security, privacy, and governance for AI systemsExcellent 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 frameworksCloud 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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