Data & AI Solutions Architect

Level: Senior (7-12 years) | Function: Data & AI | Work Model: Hybrid

Type: Individual Contributor / Player-Coach

We are seeking a Senior Data & AI Solutions Architect who can bridge business discovery, data analysis, solution architecture, data engineering, and hands-on AI/GenAI implementation.

The ideal candidate must be able to lead discovery workshops, translate ambiguous business needs into data and AI use cases, profile datasets, design end-to-end solutions, and build or prototype practical GenAI applications.

Key Responsibilities

• Lead stakeholder discovery workshops and requirements elicitation.
• Translate business problems into measurable data and AI use cases.
• Profile and analyze datasets using SQL and Python.
• Design end-to-end data and AI solutions, including C4-style architecture diagrams.
• Evaluate build-versus-buy options and technical trade-offs.
• Design and build ETL/ELT pipelines using modern orchestration and transformation tools.
• Develop and prototype GenAI solutions using LLMs, RAG, prompt engineering, embeddings, agents, and tool-use frameworks.
• Champion responsible AI, evaluation, guardrails, and human-in-the-loop practices.
• Lead initiatives from discovery through production and mentor junior team members.

Required Qualifications

• 7-12 years of experience in data analysis, data engineering, analytics consulting, or solution architecture.
• 2+ years of recent, hands-on AI/GenAI experience.
• Proven experience delivering real LLM-based applications; AI/GenAI must be demonstrated through project experience, not just resume keywords.
• Hands-on experience with RAG, prompt engineering, embeddings, and at least one agent/tool-use framework such as LangChain, LangGraph, Semantic Kernel, AutoGen, or Google ADK.
• Advanced SQL and strong Python skills.
• Experience with Power BI, Tableau, or Looker.
• Experience with ETL/ELT orchestration tools such as Airflow, Dagster, or ADF.
• Experience with dbt or an equivalent transformation framework.
• Experience with a modern data platform such as Snowflake, BigQuery, Databricks, Redshift, or Synapse.
• Experience with AWS, Azure, or Google Cloud Platform.
• Demonstrated experience producing end-to-end solution designs and leading business discovery.
• Experience delivering at least one data or AI initiative from discovery through production.

Preferred Qualifications

• Experience with MLOps/LLMOps tools such as MLflow, Weights & Biases, LangSmith, or Langfuse.
• Experience with vector databases such as Pinecone, pgvector, Weaviate, or OpenSearch.
• Experience in regulated industries.
• Data governance or Data Mesh experience.
• Consulting or client-facing experience.