Data Architect – AI Platform

Job Title: Data Architect – AI Platform

Location: Hybrid

Department: Engineering / Data Platform

About the Role

self-motivated, hands-on Data Architect

data and AI backbone

build proofs of concept (POCs)

Key Responsibilities

• Architect the Modern Data & AI Platform:

• Design a unified data architecture that supports analytics, machine learning, and AI-driven insights for both internal and customer-facing use cases.

• Build the AI Insight Stack:

• Develop the foundational components — from data ingestion and transformation to feature engineering, embeddings, and inference — that enable AI to surface patterns and insights within data.

• Be Hands-On and Experimental:

• Create POCs to validate architectural decisions, data models, and AI workflows, ensuring they deliver measurable business value.

• Bridge Data and AI Workflows:

• Design systems that make data easily consumable for both BI tools and AI pipelines — ensuring consistency and real-time readiness.

• Collaborate Across Teams:

• Partner with BI, data science, and product engineering to align data platform capabilities with analytical, AI, and product needs.

• Ensure Data Quality and Governance:

• Define standards for lineage, observability, and quality to ensure reliable, trusted data for both human and AI consumers.

• Leverage Modern Cloud and AI Stack:

• Utilize tools such as Snowflake, dbt, Airflow, Kafka, Spark, and cloud AI services (AWS SageMaker, Vertex AI, etc.) to enable scalable and efficient data operations.

• Guide Strategic Direction:

• Advise leadership on emerging data and AI technologies, influencing how the company extracts intelligence from data at scale.

Qualifications

Required:

• 8+ years of experience in

  data architecture, data engineering, or AI platform design

  .
• Proven experience

  building the end-to-end stack

  for

  AI-driven data insights

  — from raw data ingestion to model inference and insight delivery.
• Strong background in

  cloud-native data ecosystems

  (AWS, GCP, or Azure).
• Proficiency in

  Python, SQL

  , and modern data tools (Snowflake, Spark, dbt, Kafka, Airflow, etc.).
• Deep understanding of

  AI/ML workflows

  — feature stores, vector databases, model training, and deployment pipelines.
• Track record of

  building and validating POCs

  that successfully informed scalable architecture decisions.
• Excellent communication skills and ability to collaborate across data, AI, and engineering teams.

Preferred:

• Experience integrating

  Generative AI and LLM-based systems

  (RAG, embeddings, vector stores).
• Background in

  data API design

  and

  real-time data infrastructure

  for AI applications.
• Familiarity with

  MLOps / LLMOps

  frameworks (MLflow, Kubeflow, SageMaker, Vertex AI).
• Understanding of

  data governance, ethics, and responsible AI practices.

What Success Looks Like

• A unified, AI-ready data platform powering both BI insights and AI product features.
• Accelerated delivery of

  AI-driven insights

  across the company.
• Strong data foundation enabling rapid experimentation and reliable AI deployment.
• Working POCs that demonstrate the value of combining data architecture with AI intelligence.

Why Join Us

build the intelligence layer of the company

Interested candidates, please send their resumes to iqbal.kaur@birdeye.com

Regards

Iqbal Kaur