Data & AI Solutions ArchitectCSI Companies Inc Defunct • Dallas, Texas, United States
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Data & AI Solutions Architect
CSI Companies Inc Defunct
- Dallas, Texas, United States
- Dallas, Texas, United States
About
Remote within the United States; Dallas/DFW-area candidates preferred W2 only No C2C or subcontracting No visa sponsorship available now or in the future
This is an Architect-level role sitting at the intersection of business consulting, data architecture, analytics, data engineering, and modern AI enablement. The ideal candidate will be comfortable partnering with business stakeholders, translating ambiguous problems into clear data and AI use cases, profiling complex datasets, designing scalable data solutions, and helping prototype practical AI/GenAI solutions that improve workflows and decision-making. This is a strong fit for someone who can operate as both a strategic advisor and a hands‑on technical resource. Responsibilities
Partner with business and technical stakeholders to gather, clarify, and prioritize requirements Translate business problems into well‑scoped data and AI use cases with measurable outcomes Lead discovery sessions, process walkthroughs, and solution design discussions Profile datasets to evaluate quality, structure, lineage, and usability Perform exploratory analysis to validate ideas, size opportunities, and reduce delivery risk Design high‑level data and AI solutions across ingestion, storage, transformation, integration, and consumption layers Evaluate build‑vs‑buy decisions and communicate trade‑offs to technical and business leadership Design and support ETL/ELT pipelines using modern data tools and cloud platforms Define data models, schemas, and data contracts with an eye toward scalability and governance Identify opportunities to apply AI/GenAI in internal workflows, operations, and customer‑facing products Prototype and evaluate AI solutions such as RAG, copilots, agents, classification, summarization, and workflow automation Promote responsible AI practices, including evaluation, guardrails, governance, and human‑in‑the‑loop workflows Mentor analysts and junior engineers while raising standards around documentation, testing, reviews, and delivery
Required Experience
7+ years of experience across data analysis, data engineering, analytics consulting, solution architecture, or related roles Strong hands‑on experience with SQL and Python Experience with data analysis/profiling using tools such as pandas, polars, or similar Experience with at least one BI or reporting tool such as Power BI, Tableau, or Looker Hands‑on experience with modern data platforms such as Snowflake, Databricks, BigQuery, Redshift, Synapse, or similar Experience with ETL/ELT tools and orchestration frameworks such as Airflow, Dagster, Azure Data Factory, dbt, or similar Working knowledge of AWS, Azure, or GCP, including data and AI‑related services Experience producing solution designs across data ingestion, storage, processing, integration, and consumption layers Practical experience with LLM‑based applications, prompt engineering, embeddings, RAG, and agent/tool‑use frameworks Familiarity with Git, CI/CD, testing, code reviews, observability, and engineering best practices Strong stakeholder management and communication skills, including experience working with senior‑level stakeholders Ability to facilitate workshops, gather requirements, map processes, and bring structure to ambiguous business problems
Preferred Experience
Healthcare, payer/provider, hospital system, or other regulated industry experience Prior consulting or client‑facing experience Experience with MLOps or LLMOps tools such as MLflow, Weights & Biases, LangSmith, Langfuse, or similar Familiarity with vector databases such as pgvector, Pinecone, Weaviate, OpenSearch, or similar Exposure to data governance frameworks, data mesh concepts, or enterprise data strategy
Ideal Candidate The ideal candidate is a strong communicator and systems thinker who can work closely with executives, business sponsors, engineering teams, and analytics groups. This person should be comfortable digging into messy datasets, sketching solution designs, prototyping AI/GenAI use cases, and helping move ideas from concept into production. #J-18808-Ljbffr
Languages
- English
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