Senior AI/LLM Data Engineer (Technical Consultant)

TJHelpers is committed to developing strong engineering teams through mentorship, real project experience, and our “Helpers as a Service” model. We provide structured growth, hands-on practice, and a supportive environment where engineers can evolve quickly and meaningfully.

We are looking for a Senior AI/LLM Data Engineer (Technical Consultant) to join our team and help design, build, and scale modern data pipelines and retrieval systems for AI-driven products in fintech, healthcare, telecommunications, automation, and other data-intensive domains.

This role is ideal for an engineer who combines strong data engineering fundamentals with hands-on experience in LLM and RAG systems and can contribute not only through implementation, but also through architecture design, technical planning, and consulting-driven engineering decisions.

Responsibilities

• Design and develop scalable data pipelines for AI/LLM products and internal data platforms 
• Build and maintain ingestion, transformation, chunking, enrichment, indexing, and retrieval workflows 
• Prepare and structure data for RAG systems, semantic search, embeddings, and LLM evaluation workflows 
• Support fine-tuning and data preparation workflows for LLM use cases 
• Work with structured, semi-structured, and unstructured data from documents, APIs, databases, and external systems 
• Design and optimize retrieval pipelines, including metadata strategies, filtering, ranking, and relevance improvements 
• Integrate LLM-based solutions with data platforms, vector storage systems, search platforms, and backend services 
• Participate in architecture design, technical planning, and engineering decision-making for AI/LLM initiatives 
• Improve system quality, scalability, reliability, observability, and cost efficiency 
• Diagnose and resolve complex issues in production AI/data environments 
• Collaborate closely with engineers, product teams, analytics, and AI teams 
• Transform business requirements into practical AI/data engineering solutions 

Requirements

• Strong commercial experience in data engineering with hands-on work building data pipelines, ETL/ELT workflows, and distributed data processing systems 
• Hands-on experience with AI/LLM systems, RAG pipelines, embeddings, semantic search, or vector search/retrieval systems 
• Strong Python and SQL skills 
• Experience working with structured, semi-structured, and unstructured data in production environments 
• Strong understanding of data modeling, data transformation, validation, and data quality practices 
• Experience designing scalable and maintainable data workflows 
• Experience with modern data platforms and tools such as Airflow, dbt, Spark, Kafka, or similar technologies 
• Experience with vector databases or search platforms such as Pinecone, Weaviate, Milvus, Elasticsearch, or OpenSearch 
• Understanding of data preparation and optimization techniques for LLM use cases, including chunking, metadata strategies, and retrieval quality improvements 
• Experience with cloud platforms such as AWS, GCP, or Azure 
• Experience with Docker, CI/CD pipelines, and production deployment practices 
• Ability to work independently, make technical decisions, and clearly communicate trade-offs and architectural choices 
• Experience participating in technical consulting, solution design, or client-facing technical discussions 
• English level: B2 or higher 

Nice to Have

• Experience with LLM evaluation frameworks, prompt pipelines, or fine-tuning workflows 
• Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks 
• Experience with reranking, hybrid search, recommendation systems, or knowledge graphs 
• Understanding of MLOps, LLMOps, observability, and experimentation workflows 
• Experience with modern data warehouse or lakehouse platforms such as BigQuery, Snowflake, Redshift, or Databricks 
• Understanding of security, governance, and privacy practices in AI/data systems 

What We Offer

• Work on real-world AI/LLM and data-intensive products 
• Opportunity to participate in architecture, technical discovery, and solution design — not only implementation 
• Collaboration with strong engineers, architects, and product teams 
• Clear growth path toward AI Architect, Data Platform Architect, or Technical Lead roles 
• Open engineering culture focused on ownership, transparency, and continuous improvement 
• Long-term projects, flexible schedule, and fully remote work opportunities