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Join us at Seismic, a cutting-edge technology company leading the way in the SaaS industry. We specialize in delivering modern, scalable, and multi-cloud solutions that empower businesses to succeed in today’s digital era. Leveraging the latest advancements in technology, including Generative AI, we are committed to driving innovation and transforming the way businesses operate. As we embark on an exciting journey of growth and expansion, we are seeking engineering talent to join our AI team in Hyderabad, India. We are seeking a versatile Data Engineer with 2+ years of experience to build and scale the data infrastructure powering our organization. You will develop robust pipelines and optimize architectures that bridge the gap between traditional analytics and next-generation AI. In this role, you will work at the intersection of large-scale data processing and modern AI, building the critical foundations for high-performance applications and agentic workflows.
Job Responsibility:
Architect AI Data Pipelines: Design and maintain robust data ingestion and transformation pipelines tailored for LLM training, fine-tuning, and Retrieval-Augmented Generation (RAG)
Build Agentic Workflows: Utilize LangGraph to develop complex, state-managed AI agents and cyclical workflows that enhance automated user interactions
Optimize RAG Systems: Architect the retrieval layer of our AI applications, implementing efficient document embedding strategies and semantic search
Manage Vector Infrastructure: Implement and optimize Vector Databases (e.g., Pinecone, Weaviate, or Milvus) to ensure high-performance data retrieval and storage
Scale Data Models: Create scalable data schemas that support both structured and unstructured data, ensuring seamless integration with our AI services
Performance Engineering: Identify and resolve latency bottlenecks in data retrieval and embedding generation to ensure real-time AI responsiveness
Collaborate Cross-Functionally: Partner with AI Researchers and Product Managers to transition experimental AI prototypes into production-ready data products
Requirements:
2+ years of professional experience in data engineering or a backend-heavy software engineering role
Expert-level Python coding skills
Deep, hands-on experience with LangChain or LangGraph to build sophisticated multi-step chains and agentic systems
Proven experience implementing and tuning Vector Databases for high-volume RAG pipelines
Strong understanding of traditional data modeling, ETL/ELT processes, and working with SQL/NoSQL databases
Solid grasp of embedding models, tokenization, and modern information retrieval techniques
Thrive in fast-paced environments and enjoy staying updated with the rapidly evolving landscape of GenAI and search technologies