We’re hiring a motivated Junior/Strong Junior (Middle-ready) AI Engineer to join a team delivering multiple AI projects across different domains. You’ll work under experienced engineers who lead architecture, while you implement hands-on components across data engineering, LLM/RAG, and AWS/MLOps. One of the likely project types is a research assistant with LLM-based extraction and citation-backed Q&A.
Build and support data ingestion & ETL (APIs/DBs/files), parsing, validation, and transformations;
Contribute to domain modeling & schema design (entities/relationships, migrations/versioning support);
Implement LLM/NLP pipelines (structured extraction, classification, summarization) with basic monitoring and QA;
Help build RAG backends and integrate assistants with apps (retrieval, grounding, citations);
Develop/extend backend APIs & metadata stores consumed by internal tools and UIs;
Support AWS/MLOps/DevOps work (deployments, CI/CD, logging/monitoring, runbooks) with mentorship.
Python, SQL, ETL/pipeline fundamentals;
Familiarity with ML/DS basics;
Hands-on AWS exposure;
Familiarity with LLMs (prompting, structured outputs, embeddings/RAG basics);
High motivation to learn and work on AI projects.
Airflow/Dagster/Prefect, Docker, Terraform/CDK;
Vector DB/search (pgvector/OpenSearch/Pinecone/etc.);
Basic UI/internal tooling (React/Streamlit).