Principal Solution Architect - Data and AI Platform

Nexylum Global Llc

United States

4 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Unity 3d Artificial Intelligence Business Analytics Applications Application Frameworks Audit Trail Microsoft Azure Cloud Engineering Continuous Integration Data Architecture Information Engineering Data Infrastructure Data Security

+26 more

Software Design Patterns Github Metadata Operational Databases Performance Tuning Role-Based Access Control Recommender Systems Search Technologies SQL Databases Azure Service Bus Azure Data Factory Large Language Models Multi-Agent Systems Prompt Engineering Apache Spark Data Layers Data Lakes AI Platforms Pyspark Collibra Data Analytics Data Management Machine Learning Operations Data Delivery Api Management Databricks

Job description

Define and drive the Data and AI platform architecture using Databricks, Delta Lake, Unity Catalog, and modern lakehouse design patterns.
Architect secure LLM and GenAI enablement patterns, including RAG, embeddings, vector search, semantic search, prompt orchestration, model serving, grounding, and AI evaluation.
Design agentic AI capabilities to support data platform operations such as metadata discovery, catalog enrichment, lineage analysis, data quality investigation, documentation generation, pipeline troubleshooting, test generation, and operational runbook support.
Establish architecture standards for AI-ready data products, certified metrics, semantic layers, business definitions, metadata, lineage, data contracts, and reusable data engineering patterns.
Guide modernization of key workloads into a scalable Databricks Lakehouse architecture using Bronze, Silver, and Gold data zones, governed Delta patterns, workflows, observability, and CI/CD-enabled delivery.
Define responsible AI and governance controls, including human-in-the-loop approvals, prompt and response governance, auditability, least-privilege access, entitlement-aware responses, and sensitive data protection.
Partner with AI/ML and data engineering teams to productionize AI-driven insights and recommendations across business domains such as merchant analytics, authorization, disputes, chargebacks, interchange, risk, fraud, and operational anomalies.
Provide technical leadership through architecture reviews, solution design, standards creation, proof-of-concepts, reusable frameworks, and implementation guidance.
Collaborate with product and business stakeholders to translate strategic data and AI needs into practical platform capabilities and delivery roadmaps.

Requirements

10+ years of experience in data architecture, solution architecture, data engineering, analytics platforms, or AI/data platforms.
Strong hands-on Databricks experience, including Delta Lake, Unity Catalog, Spark/PySpark, SQL, Databricks Workflows, medallion architecture, performance optimization, and production data engineering patterns.
Experience designing and implementing LLM/GenAI solutions, including RAG, vector search, embeddings, conversational AI, prompt engineering, model serving, AI evaluation, and hallucination mitigation.
Understanding of agentic AI architecture, including tool use, workflow automation, agent guardrails, approval patterns, audit trails, and safe execution models.
Strong knowledge of data architecture concepts such as data products, semantic layers, data contracts, metadata, cataloging, lineage, observability, data quality, and governance.
Experience designing secure data platforms using RBAC, ABAC, row-level security, column-level security, masking, encryption, audit logging, and entitlement-aware data delivery.
Ability to create architecture diagrams, standards, decision records, implementation playbooks, and reusable design patterns.
Strong communication and influencing skills with the ability to work across engineering, AI/ML, product, governance, security, operations, and executive stakeholders., * Experience with Databricks Mosaic AI, MLflow, Model Serving, Vector Search, Feature Store, Lakehouse Monitoring, or advanced Unity Catalog capabilities.
Experience with Azure data and AI services such as ADLS, Synapse, Data Factory, Event Hubs, Azure OpenAI, Azure AI Search, Azure API Management, Azure DevOps, or GitHub Actions.
Background in payments, merchant acquiring, financial services, merchant analytics, authorization, disputes, chargebacks, interchange, settlement, funding, risk, or fraud.
Familiarity with LLM and agent frameworks such as LangChain, LangGraph, Semantic Kernel, LlamaIndex, AutoGen, CrewAI, or similar technologies.
Experience with enterprise cataloging and governance tools such as Microsoft Purview, Collibra, Alation, Informatica, or Unity Catalog.
Experience building AI assistants, data copilots, analytics copilots, recommendation engines, or self-service analytics platforms.
Databricks, Azure, AI/ML, data engineering, or cloud architecture certifications are a plus.