Jobs via Dice
Solution Architect (Data modernization| Cloud Architect |Data & Analytics)
Jobs via Dice, Mount Laurel, New Jersey, United States
Solution Architect (Data Modernization | Cloud Architect | Data & Analytics) – Mount Laurel, NJ (Onsite). Full‑time position.
Key Responsibilities
Architect scalable, secure, and high‑performance solutions using Microsoft Azure services, incorporating Gen‑AI and LLM components where appropriate.
Create detailed architecture blueprints, solution diagrams, and technical documentation for cloud and data solutions.
Design large‑scale data processing and analytics platforms leveraging Azure Databricks and Apache Spark.
Lead implementation of Databricks‑based and Azure‑based solutions, ensuring they follow best practices and meet business requirements.
Lead design and delivery of Gen‑AI LLM solutions including use cases such as summarization, question‑answering, knowledge augmentation, generation, and intelligent automation.
Design and implement CI/CD and MLOps practices for data pipelines and model lifecycle management using Azure DevOps and Azure ML.
Provide technical leadership and guidance across the project lifecycle, including prompt engineering best practices, safety and hallucination mitigation strategies, and model governance.
Ensure robust security, privacy, and compliance measures for Gen‑AI and data solutions, including identity management, encryption, data handling, and access controls.
Optimize cloud and model‑serving resources for performance, cost, and reliability, including scalable inference, batching, and autoscaling strategies.
Monitor model performance and data pipelines in production, establishing alerting and metrics for accuracy, bias, latency, and cost.
Collaborate with stakeholders to gather requirements, translate them into technical solutions, and advocate responsible use of Gen‑AI.
Stay current with the latest Azure services (Azure OpenAI Service, Cognitive Services), LLM developments, and industry trends to recommend improvements.
Requirements
Bachelor's degree in Computer Science, Engineering, or a related field.
15+ years of experience in data engineering, cloud architecture, or a closely related discipline.
Deep hands‑on experience with Databricks and Apache Spark.
Familiarity with Azure OpenAI Service, Azure Cognitive Services, or equivalent managed ML/LLM platforms.
Strong proficiency in Python.
Solid SQL skills and experience with relational and analytical databases.
Proven experience with cloud platforms, with a strong focus on Microsoft Azure.
Experience with modern data warehousing patterns and technologies (e.g., Delta Lake, Lakehouse architectures).
Understanding of data governance, privacy, security best practices, and ethical considerations for Gen‑AI.
Experience implementing MLOps for model versioning, CI/CD for models, automated testing, and monitoring.
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Engineering and Information Technology
Industries
Software Development
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Key Responsibilities
Architect scalable, secure, and high‑performance solutions using Microsoft Azure services, incorporating Gen‑AI and LLM components where appropriate.
Create detailed architecture blueprints, solution diagrams, and technical documentation for cloud and data solutions.
Design large‑scale data processing and analytics platforms leveraging Azure Databricks and Apache Spark.
Lead implementation of Databricks‑based and Azure‑based solutions, ensuring they follow best practices and meet business requirements.
Lead design and delivery of Gen‑AI LLM solutions including use cases such as summarization, question‑answering, knowledge augmentation, generation, and intelligent automation.
Design and implement CI/CD and MLOps practices for data pipelines and model lifecycle management using Azure DevOps and Azure ML.
Provide technical leadership and guidance across the project lifecycle, including prompt engineering best practices, safety and hallucination mitigation strategies, and model governance.
Ensure robust security, privacy, and compliance measures for Gen‑AI and data solutions, including identity management, encryption, data handling, and access controls.
Optimize cloud and model‑serving resources for performance, cost, and reliability, including scalable inference, batching, and autoscaling strategies.
Monitor model performance and data pipelines in production, establishing alerting and metrics for accuracy, bias, latency, and cost.
Collaborate with stakeholders to gather requirements, translate them into technical solutions, and advocate responsible use of Gen‑AI.
Stay current with the latest Azure services (Azure OpenAI Service, Cognitive Services), LLM developments, and industry trends to recommend improvements.
Requirements
Bachelor's degree in Computer Science, Engineering, or a related field.
15+ years of experience in data engineering, cloud architecture, or a closely related discipline.
Deep hands‑on experience with Databricks and Apache Spark.
Familiarity with Azure OpenAI Service, Azure Cognitive Services, or equivalent managed ML/LLM platforms.
Strong proficiency in Python.
Solid SQL skills and experience with relational and analytical databases.
Proven experience with cloud platforms, with a strong focus on Microsoft Azure.
Experience with modern data warehousing patterns and technologies (e.g., Delta Lake, Lakehouse architectures).
Understanding of data governance, privacy, security best practices, and ethical considerations for Gen‑AI.
Experience implementing MLOps for model versioning, CI/CD for models, automated testing, and monitoring.
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Engineering and Information Technology
Industries
Software Development
#J-18808-Ljbffr