Goldenpick Technologies

41 Goldenpick Technologies Jobs Hiring Near You

Remote 100% Must have * Strong knowledge of IVR systems and telecommunications platforms (ERSA, Replicant, Seamless). * Experience with QA methodologies, test planning, and execution. * Proficiency ...

Senior AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Stay up to date with emerging AI technologies and frameworks * Evaluate and implement GenAI, LLMs, and prompt engineering techniques * Prototype and experiment with new AI-driven solutions Skills ...

Senior Desktop Support

Dallas, TX · On-site

$20 - $25.50/hr

Provide assistance with conference room technology (pre-meeting testing and in-meeting troubleshooting). * Assist with device installations or moves (disconnect/reconnect), managed print setup and ...

Scrum Master (Jira)

Orlando, FL · On-site

$48 - $64.25/hr

Bachelor's degree in Computer Science, Information Technology, Business, or a related field (or equivalent experience). * 5+ years of experience as a Scrum Master in Agile software development ...

Position Details: Role: CREO Modeler Location: Houston, TX (Hybrid) An advanced level Modeler position for candidates with extensive CREO/ Hecsalv or relevant software experience. Responsible for the ...

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Infographic showing various job openings at Goldenpick Technologies in the United States as of July 2026, with employment types broken down into 14% Full Time, and 86% Contract. Highlights an 86% Physical, and 14% Remote job distribution.

AI Senior Technology Architect

Goldenpick Technologies

Irving, TX • On-site

Contractor

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Role Overview

We are looking for a visionary AI Senior Technology Architect to lead enterprise-scale AI transformation initiatives. This role requires deep expertise in Generative AI, Agentic AI systems, AI infrastructure, and cloud-native architectures, with a strong focus on delivering scalable, high-performance AI solutions and driving business impact.

This role is critical to driving AI-first enterprise strategy, enabling next-generation capabilities through Agentic AI, LLM ecosystems, and edge intelligence while delivering measurable business value.

Key Responsibilities

·         Define and govern enterprise AI architecture including LLMs, RAG, Agentic AI, and Edge AI systems.

·         Establish reference architectures for cloud-native AI, GPU-based inferencing, and distributed workloads.

·         Architect and deploy LLM-powered solutions using RAG, embeddings, vector databases, and orchestration frameworks.

·         Design Agentic AI workflows leveraging tools such as LangChain, LangGraph, Azure AI, and Databricks.

·         Lead AI infrastructure strategy including GPU optimization and high-performance compute environments.

·         Build and scale AI platforms across AWS, Azure, and GCP ecosystems.

·         Lead development of advanced AI/ML models across NLP, computer vision, graph ML, and forecasting domains.

·         Architect Edge AI solutions for low-latency, distributed decision-making systems.

·         Establish governance for responsible AI, security, and compliance.

·         Mentor teams and drive innovation and capability development.

Required Qualifications

·         15+ years of experience in AI/ML, Data Science, or Technology Architecture.

·         Strong expertise in Generative AI, LLMs, RAG, and Agentic AI systems.

·         Proficient in Python, APIs, microservices, and data engineering frameworks.

·         Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies.

·         Deep understanding of AI infrastructure including GPU optimization and benchmarking.

·         Proven ability to lead large-scale transformation programs.

Preferred Qualifications & Experience

·         Experience in banking, telecom, healthcare, energy, or supply chain domains.

·         Exposure to Edge AI, O-RAN architectures, and distributed systems.

·         Advanced degree (PhD/Master’s) in AI, Data Science, or related field.

·         Experience in Enterprise adoption of AI platforms and architecture standards.

·         Experience in Scalable deployment of AI solutions delivering measurable outcomes.