AI Solution Architect

HTC Global Services is seeking an experienced AI Solution Architect to design and implement enterprise-grade AI solutions powered by Large Language Models (LLMs) and agentic AI technologies. The role involves translating business challenges into scalable, secure, production-ready AI architectures while providing technical leadership throughout the solution lifecycle.

Key Responsibilities

Identify AI opportunities, assess feasibility, and translate business requirements into technical architectures.

Lead end-to-end architecture for LLM-based and agentic AI applications, including RAG pipelines, agent orchestration, MCP integrations, and tool calling.

Develop prototypes and evaluate AI models, platforms, and frameworks through structured experiments and performance benchmarks.

Design secure, scalable AI solutions aligned with enterprise architecture, data governance, and compliance requirements.

Establish standards for prompt engineering, model evaluation, observability, versioning, deployment, and production monitoring.

Guide and mentor AI engineers, review solution designs, and resolve technical challenges.

Collaborate with security, legal, data governance, and enterprise architecture teams.

Recommend technology adoption strategies and build-versus-buy decisions based on business value and technical feasibility.

Key Requirements

10+ years of technical experience, including recent hands-on experience designing and deploying LLM-based and agentic AI solutions in production.

Strong expertise in LLMs, agentic AI architectures, agent orchestration, Retrieval-Augmented Generation (RAG), vector databases, and Model Context Protocol (MCP).

Enterprise architecture and integration experience across APIs, event-driven architectures, data pipelines, distributed systems, and cloud platforms.

Proficiency in Python; experience with TypeScript, C#, or Java is preferred.

Knowledge of prompt engineering, AI evaluation frameworks, model performance assessment, observability, and production deployment practices.

Experience delivering solutions in regulated or security-conscious environments.

Strong stakeholder management, communication, and technical leadership skills.

Preferred Background

Experience in machine learning or data science is an advantage but not mandatory.