AI Data Engineer in Hyderabad, भारत

Description : Role : AI Data Engineer- Location : Rai Durg, Hyderabad- Work mode- Hybrid model working (3 days work from office)- Experience : 5 - 8 Years (Minimum 5 years- AI Data Engineer)- Mandatory Skills : DVC (Data Version Control) and Airflow, Apache Spark, Flink, and Kafka, Advanced level Python and AI logic and Rust (or C++), Vector Database Mastery like configuration of HNSW indexes, scalar quantization, and metadata filtering strategies- Qualification : Bachelor of Engineering - Bachelor of Technology (B.E./B.Tech.)- Notice period : Immediate / early joiners (Max. 15-30 days)- Interview Process : 2 - 3 Technical roundsImportant Note : - We are currently prioritizing immediate / early joiners (maximum 15-30 days- notice period above 30 days will be automatically rejected.).- All mandatory technical skills must be clearly highlighted within the project descriptions in your resume, not just listed in the Skills or Roles & Responsibilities sections .Position Overview : We are seeking a hardcore, hands-on AI Data Engineer to build the high-performance data infrastructure required to power autonomous AI agents. You won't just be moving data from A to B; you will be architecting Dynamic Context Windows, managing Real-time Semantic Indexes, and building Self-Cleaning Data Pipelines that feed our "Super Employee" https://jobeax.com/link/qgXi820YIqv76aTa Responsibilities : - Vector & Graph ETL : Design and maintain pipelines that transform unstructured data (PDFs, emails, logs, chats) into optimized embeddings for Vector Databases (Pinecone, Weaviate, Milvus).- Semantic Data Modeling : Engineer data structures that optimize for Retrieval-Augmented Generation (RAG), ensuring agents find the "needle in the haystack" in milliseconds.- Knowledge Graph Construction : Build and scale Knowledge Graphs (Neo4j) to represent complex relationships in our trading and support data that standard vector search misses.- Automated Data Labeling & Synthetic Data : Implement pipelines using LLMs to auto-label datasets or generate synthetic edge cases for agent training and evaluation.- Stream Processing for Agents : Build real-time data "listeners" (Kafka/Flink) that feed live context to agents, allowing them to react to market or support events as they happen.- Data Reliability & "Drift" Detection : Build monitoring for "Embedding Drift", identifying when the statistical distribution of your data changes and the agent's "knowledge" becomes https://jobeax.com/link/Ihs9cu3PQNeDshwT : - Vector Database Mastery : Expert-level configuration of HNSW indexes, scalar quantization, and metadata filtering strategies within Pinecone, Milvus, or Qdrant.- Advanced Python & Rust : Proficiency in Python for AI logic and Rust (or C++) for high-performance data processing and custom embedding functions.- Big Data Ecosystem : Hands-on experience with Apache Spark, Flink, and Kafka in a high-throughput environment (Trading/FinTech preferred).- LLM Data Tooling : Deep experience with https://jobeax.com/link/1lOjIu2fd7dmCYhc, LlamaIndex, or LangChain for document parsing and chunking strategy optimization.- MLOps & DataOps : Mastery of DVC (Data Version Control) and Airflow/Prefect for managing complex, non-linear AI data workflows.- Embedding Models : Understanding of how to fine-tune embedding models (e.g., BGE, Cohere, or OpenAI) to better represent domain-specific (Trading) https://jobeax.com/link/B7JgmJnk9Gb8T8WR qualifications : - Chunking Strategy Architect : You don't just "split text." You implement Semantic Chunking and Parent-Child retrieval strategies to maximize LLM context relevance.- Cold/Warm/Hot Storage Strategy : Managing cost and latency by tiering data between Vector DBs (Hot), SQL/NoSQL (Warm), and S3/Data Lakes (Cold).- Privacy & Redaction Pipelines : Building automated PII (Personally Identifiable Information) redaction into the ingestion layer to ensure agents never "see" or "leak" sensitive user https://jobeax.com/link/jxiWW6aO1hr4DktS Join ?- Opportunity to lead transformative initiatives, modernizing legacy systems and shaping the future of trading technology.- Work with cutting-edge technologies in a dynamic, fast-paced environment.- Competitive compensation, professional growth opportunities, and the chance to work with industry-leading experts. (ref:hirist.tech)