We are seeking a visionary and execution-focused Senior Data Science Engineer to spearhead the design, development, and scaling of our next-generation intelligent systems. This role is built for a technical heavyweight who sits at the intersection of Advanced Generative AI (RAG - Multi-Agent Systems), High-Performance Data Architectures, and Enterprise Cloud Engineering.

You will own the optimization of our transactional and search layers (ELK - PostgreSQL), build resilient orchestration pipelines, and deploy secure, hybrid-cloud solutions across AWS, Azure, and GCP.

What You'll Do :

High-Performance Data - Search Architecture :

- Enterprise Log - Search Analytics : Architect, configure, and maintain the ELK Stack (Elasticsearch, Logstash, Kibana) to ingest, parse, index, and visualize massive multi-source data streams, enabling real-time observability and sub-second semantic/lexical search.

- PostgreSQL Optimization : Act as the subject matter expert for the relational database layer. Write complex queries, stored procedures, functions, and triggers. Diagnose bottlenecks, execute query optimization, index tuning, and oversee database backup, recovery, and archiving strategies.

AI Engineering - Agentic Systems :

- Autonomous Agents - Tool Integration : Design, productize, and mature task-oriented AI agents and multi-agent orchestrations that execute complex, deterministic workflows rather than simple conversational chat completions.

- Production RAG Architectures : Build and optimize end-to-end Retrieval-Augmented Generation (RAG) pipelines using advanced chunking, metadata tagging, hybrid search, and reranking strategies over massive structured and unstructured datasets.

- Model Evaluation - Frameworks : Deploy and monitor Large Language Models (LLMs) and Large Multimodal Models (LMMs) for text, image, audio, and video analytics. Productize solutions using enterprise-grade frameworks (e.g., LangChain, Langgraph, Semantic Kernel, or custom orchestration runtimes).

Cloud-Native Deployment - Infrastructure :

- Multi-Cloud Excellence : Design and deploy highly available, secure, and compliant AI workloads across AWS, Azure, and GCP.

- MLOps - Containerization : Enforce strict containerization using Docker and automate pipeline orchestration. Collaborate with DevOps to implement secure, automated CI/CD infrastructures and infrastructure-as-code (IaC).

Leadership - Iterative Delivery :

- Technical Ownership : Take end-to-end ownership of major features and core architecture components, driving technical decisions from concept to production.

- Agile Mentorship : Embrace an iterative, fast-paced development culture. Mentor junior engineers, conduct robust code reviews, and advocate for engineering best practices.

What We're Looking For :

- Python Mastery : 4+ years of professional experience in modern Python development with a strict emphasis on writing clean, maintainable, production-ready code.

- Data Layer Expertise : 2+ years of deep hands-on experience with Elasticsearch/ELK Stack (cluster management, pipeline routing, and indexing) and PostgreSQL (advanced query optimization, performance tuning, structural design).

- Generative AI - NLP : 2+ years of experience putting deep learning, NLP, or LLM-based solutions into enterprise production. Solid understanding of embedding spaces, vector databases, and agentic tool-calling patterns.

- Cloud - DevOps : Demonstrated proficiency in provisioning and managing resources within AWS, Azure, and GCP. Solid experience with Docker and production-grade orchestration tools.

- Education : Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a highly quantitative field.

Office Timing : 1pm to 9pm IST

Office Location : Manyata Tech Park, Bangalore, India

Work Model : Office/Hybrid