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# Senior Architect - Data Engineering

- **Company:** Goldenpick Technologies
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Applications Architecture, Microsoft Azure, BigQuery, Cloud Computing, Continuous Integration, Data Architecture, Information Engineering, Identity and Access Management, Python (Programming Language), Machine Learning, Metadata, OAuth, OpenID, Role-Based Access Control, OpenAI, Microsoft Copilot, Search Technologies, TypeScript, Enterprise Search, Pinecone, Google Cloud, Data Ingestion, Retrieval-Augmented Generation, Large Language Models, Snowflake, Prompt Engineering, Deep Learning, Vertex AI Vector Search, Pgvector, AI Platforms, Kubernetes, Weaviate, Milvus, Graphql, Azure AI, Api Design, Google Gemini, GPT, Api Management, Serverless Computing, OpenSearch, Databricks, Microservices
- **Published:** November 12, 2026
- **Apply:** https://www.dice.com/job-detail/5f0a49e1-0206-4fd3-ae58-8a4a045217eb

## About the Role

* Experience: 11 to 16 years in software, data and solution architecture, including at least 3 years designing and delivering production GenAI/LLM solutions.
 * Hands-on engineering: Strong Python (plus Java, TypeScript or similar), REST/GraphQL APIs and event-driven integration. Current in code, not only diagrams.
 * RAG and vector search: Demonstrated delivery of RAG systems with vector databases (e.g., Pinecone, pgvector, Azure AI Search, Vertex AI Vector Search, OpenSearch, Weaviate or Milvus). Retrieval quality tuning and evaluation.
 * LLM platforms: Hands-on with Anthropic, OpenAI and Gemini APIs, including tool/function calling, structured outputs, prompt engineering, context management and cost control.
 * Cloud: Production experience on Google Cloud Platform (strongly preferred), Azure or AWS: compute and containers (Kubernetes), managed AI services (Vertex AI, Azure OpenAI/AI Foundry, Bedrock), storage, serverless and CI/CD.
 * Data architecture: Data modelling, lakehouse/warehouse patterns, ingestion pipelines, metadata, lineage and data quality. Snowflake, BigQuery or Databricks experience.
 * Application architecture: Microservices, API design, integration patterns, resilience and non-functional requirements.
 * Security and governance: RBAC, identity (OAuth2/OIDC, Entra ID, IAM), APIM gateways, encryption and compliance (e.g., HIPAA, GDPR, SOC 2).
 * Architecture governance: Proven track record presenting to and securing approval from ARBs, with clear ADRs and trade-off analysis.
 * Communication: Clear written and verbal communication with executives and engineers. Experience leading without direct authority.

## Description

It is a remote position in US. Please note 0 to 25% travek may be needed to visit client in US. And the travel will be based on the need.
Skills : Azure AI, GenAI Architect, Architect, Llm guardrails, Deep Learning, ChatGPT, OpenAI, Data Engineer, Python, Microsoft Copilot, Machine Learning.