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# GCP AI Architect (Remote)

- **Company:** Cognizant Technology Solutions Corporation
- **Location:** Dallas, TX, United States
- **Salary:** $160,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Cloud Computing, Information Leak Prevention, Graph Database, Machine Learning, Metadata, Search Technologies, Unstructured Data, Workflow Management Systems, Data Logging, Feature Engineering, Retrieval-Augmented Generation, Delivery Pipeline, Large Language Models, Multi-Agent Systems, Prompt Engineering, IT Architecture, Generative AI, Indexer, Containerization, Kubernetes, Machine Learning Operations, Api Design, GPT, Software Version Control, Data Pipelines, Unsupervised Learning, Microservices
- **Published:** September 4, 2026
- **Apply:** https://www.dallasjobsite.com/job.asp?id=3377314162&tx=VT6156TYT&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Strong understanding of Generative AI models (LLMs, multimodal models, embeddings).
 * Hands-on experience with foundation models (e.g., GPT-style, Claude-style, LLaMA-style) and model adaptation techniques.
 * Expertise in prompt engineering , prompt orchestration , and agent-based frameworks .
 * Solid grounding in machine learning fundamentals , including supervised/unsupervised learning, evaluation metrics, and inference optimization.

AI Architecture & System Design

 * Ability to design scalable, modular GenAI architectures for production use.
 * Experience with:
 * RAG (Retrieval-Augmented Generation) architectures
 * Vector databases (semantic search, embeddings indexing)
 * Multi-agent systems and workflow orchestration
 * Strong understanding of low-latency inference , model routing , and fallback strategies .
 * Knowledge of event-driven , microservices , and API-first architectures .

Product Engineering & Integration

 * Experience integrating GenAI capabilities into customer-facing and internal products .
 * Ability to translate product requirements into AI-driven capabilities and technical designs.
 * Familiarity with A/B testing , feature flags, and iterative product releases involving AI.

Data & Knowledge Engineering

 * Proficiency in data pipelines , feature engineering , and unstructured data processing .
 * Experience with:
 * Knowledge graphs
 * Metadata-driven architectures
 * Document ingestion and chunking strategies
 * Strong understanding of data quality, provenance, and governance for AI systems.

Cloud, MLOps & Platform Skills

 * Strong experience in cloud-native environments (GCP).
 * Familiarity with MLOps practices , including:
 * Model versioning
 * Deployment pipelines
 * Monitoring, logging, and drift detection
 * Experience with containerization , Kubernetes , and CI/CD pipelines.
 * Knowledge of inference optimization and cost-control strategies.

Security, Privacy & Responsible AI

 * Understanding of AI security risks (prompt injection, data leakage, model abuse).
 * Experience implementing guardrails , content filters , and policy enforcement .
 * Knowledge of responsible AI practices , including explainability, bias mitigation, and compliance.
 * Familiarity with data privacy regulations (e.g., GDPR, enterprise governance standards).



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