Position: Data & AI Architect
Location: Houston , TX - Hybrid
Duration - 14 months
Job Summary
We are looking for an experienced Data & AI Architect to design and implement enterprise-scale data and AI solutions. The ideal candidate will have strong expertise in data architecture, cloud data platforms, data engineering, machine learning, Generative AI, and enterprise data governance.
The candidate will be responsible for defining end-to-end data and AI architecture, building scalable data platforms, integrating AI/ML capabilities, and enabling data-driven business transformation. This role requires strong technical leadership, hands-on architecture experience, and the ability to collaborate with engineering teams, business stakeholders, and senior leadership.
Key Responsibilities
- Define and implement enterprise data and AI architecture strategies aligned with business objectives.
- Design scalable, secure, and high-performance data platforms across cloud environments such as AWS, Azure, or Google Cloud Platform.
- Architect modern data lake, data warehouse, lakehouse, and data mesh solutions.
- Design and implement data ingestion, transformation, integration, and processing pipelines using batch and real-time technologies.
- Develop enterprise data models, data architecture standards, and reusable architectural patterns.
- Architect AI/ML and Generative AI solutions, including LLMs, RAG, vector databases, and AI-powered applications.
- Integrate machine learning models and AI services into enterprise data platforms and business applications.
- Evaluate and implement frameworks for model development, deployment, monitoring, and lifecycle management (MLOps).
- Design data governance, metadata management, data cataloging, data lineage, data quality, and data security frameworks.
- Establish best practices for data privacy, access control, regulatory compliance, and responsible AI.
- Work with Data Engineers, Data Scientists, ML Engineers, DevOps teams, and business stakeholders to deliver end-to-end solutions.
- Assess existing data ecosystems, identify gaps, and recommend modernization and cloud migration strategies.
- Define technology roadmaps, architecture blueprints, reference architectures, and technical standards.
- Evaluate emerging technologies, tools, and frameworks in data engineering, AI, and cloud computing.
- Provide technical leadership, conduct architecture reviews, mentor engineering teams, and ensure adherence to architectural standards.
- Optimize data platform performance, scalability, reliability, and cloud infrastructure costs.
Required Skills
- 10+ years of experience in Data Engineering, Data Architecture, AI/ML, or related technology roles.
- Strong experience designing and implementing enterprise-scale data architectures.
- Expertise in at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (Google Cloud Platform).
- Strong understanding of modern data architecture, including Data Lakes, Data Warehouses, Lakehouse, and Data Mesh.
- Hands-on experience with data engineering technologies such as Apache Spark, Databricks, Snowflake, BigQuery, Redshift, or Synapse.
- Strong knowledge of ETL/ELT pipelines, data integration, data modeling, and distributed data processing.
- Experience with Python, SQL, and data processing frameworks.
- Strong understanding of AI/ML concepts, machine learning workflows, and model deployment.
- Experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and vector databases.
- Knowledge of MLOps, model lifecycle management, CI/CD, and model monitoring.
- Experience designing data governance, metadata management, data quality, lineage, and security solutions.
- Strong knowledge of cloud-native architecture, microservices, APIs, and distributed systems.
- Experience with architecture documentation, solution design, technical roadmaps, and design reviews.
- Excellent communication, stakeholder management, and technical leadership skills.
Preferred Skills
- Experience with cloud AI/ML services such as Azure AI Foundry, Azure Machine Learning, Amazon SageMaker, Google Vertex AI, or equivalent platforms.
- Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
- Knowledge of vector databases such as Pinecone, Weaviate, Milvus, FAISS, or Azure AI Search.
- Experience with agentic AI, AI agents, and multi-agent architectures.
- Experience with Databricks, Delta Lake, Apache Iceberg, or Hudi.
- Knowledge of real-time data streaming technologies such as Kafka, Spark Streaming, or Flink.
- Experience with data catalog and governance tools such as Microsoft Purview, Google Dataplex / Knowledge Catalog, Collibra, or Alation.
- Experience with Terraform, Kubernetes, Docker, and cloud infrastructure automation.
- Knowledge of Responsible AI, AI risk management, model explainability, and data privacy.
- Experience with FinOps, cloud cost optimization, and enterprise-scale platform modernization.
- Familiarity with Agile, DevOps, and DataOps practices.
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Pooja Jaiswal Technical Recruiter
Aptino, Inc.
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