AI Infrastructure Architect

About the role

Accenture is seeking an AI Infrastructure Architect to design and deliver enterprise‑grade data architectures that power GenAI, large language model (LLM) applications, and agentic AI solutions. The role bridges data engineering, data science, and AI, ensuring robust, production‑ready pipelines for both structured and unstructured data across multiple Bulgarian locations.

Key responsibilities

• Design end‑to‑end data architectures for GenAI and agentic AI use cases, covering ingestion, transformation, storage, and access layers.
• Build and optimise batch and real‑time pipelines for diverse data types.
• Establish AI‑ready data foundations, including feature engineering, embeddings generation, and vector indexing.
• Define scalable data models and access patterns tailored to LLM‑driven systems.
• Maintain data governance, lineage, security, and compliance across cloud platforms.
• Collaborate with data scientists, ML engineers, and platform teams to operationalise AI solutions.
• Translate business requirements into future‑proof data architectures.

Required profile

• 4‑6 years of experience in data engineering or data architecture.
• At least 2 years focused on GenAI, LLMs, or related AI technologies.
• Strong background in cloud data platforms (Azure, Google Cloud, or AWS).
• Hands‑on experience with Python and SQL.

Required skills

• Python
• SQL
• Snowflake
• Azure Synapse, Azure Data Factory, Azure Fabric
• Google BigQuery, Dataflow, Vertex.ai
• AWS Redshift, AWS Glue
• Airflow, dbt, Kafka, Databricks
• Vector databases such as Pinecone, Weaviate, FAISS