AI Infrastructure Architect

About the job Accenture is a global professional services company with leading capabilities in digital, cloud, and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song — all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 740,000+ people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. The role is open in various locations such as Sofia, Plovdiv, Varna, Ruse and Burgas. We are seeking a highly skilled Data Architect Consultant to design and deliver scalable, enterprise-grade data architectures that enable advanced analytics, GenAI, and agentic AI solutions. This role sits at the intersection of data engineering, data science, and AI, requiring hands-on expertise in building robust data ecosystems that support LLM-driven applications, RAG pipelines, and intelligent agent workflows in production environments. Key Responsibilities: Design and implement end-to-end data architectures supporting GenAI and agentic AI use cases, including data ingestion, transformation, storage, and access layers Build and optimize batch and real-time data pipelines for structured and unstructured data Enable AI-ready data foundations, including feature engineering, embeddings generation, and vector indexing Define scalable data models and access patterns tailored for LLM and agent-based systems Ensure strong data governance, lineage, security, and compliance across platforms Collaborate with data scientists, ML engineers, and platform teams to operationalize AI solutions Translate business requirements into scalable, future-proof data architectures Experience Level: 4-6 years in Data Engineering/ Data Architecture with 2+ years focused on GenAI/LLMs Strong experience in data architecture, data engineering, and analytics in cloud environments Proficiency in Python and SQL, with hands-on experience in platforms like Snowflake and distributed data processing Experience with modern data platforms: Azure (Synapse, Data Factory, Fabric), Google Cloud (BigQuery, Dataflow, Vertex.ai), or AWS (Redshift, Glue) Expertise in data pipeline orchestration and transformation tools such as Airflow, dbt, Kafka, and Databricks Solid understanding of both structured and unstructured data processing AI & GenAI Expertise: Experience supporting LLM-based applications, including RAG architectures and embeddings workflows Familiarity with vector databases such as Pinecone, Weaviate, or FAISS Knowledge of AI orchestration frameworks such as LangChain, LlamaIndex, or Semantic Kernel Experience integrating with enterprise AI platforms such as Azure AI Foundry or Google Vertex AI is a strong advantage Nice to have: Strong understanding of data governance, security, and regulatory requirements Experience working in cross-functional teams delivering enterprise AI solutions Ability to bridge technical and business stakeholders and communicate complex concepts clearly The Rest of the qualities, you know them: Fluent in English – verbal & written Ability to work independently, demonstrating high-level organizational and execution skills Strong analytical, problem-solving, and time management skills. Proactive mindset and willingness to cross-functional collaboration Very good attention to detail and meeting deadlines Benefits: Certification Career Counselling 25 day paid vacation Flexible home office policy Options to buy shares Luxury health & dental insurance Food vouchers Multisport cards Employee Assistance Program