AI Architect; GenAI​/MLOps

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 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., Lang Chain, Llama Index)

Strong Python skills and fluency in ML frameworks (PyTorch, Tensor Flow, scikit-learn)

Deep experience with at least one major cloud (AWS, Azure, or GCP) and its AI services (e.g., Sage Maker, 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, Open Search) 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
• 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.