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Grid Dynamics - Senior Software Engineer - Generative AI Job Opening In Bengaluru – Now Hiring GRID DYNAMICS PRIVATE LIMITED


Job description

<p><p><b>Experience : </b> 5+ years.<br/><br/> Open for Bangalore/Hyderabad.<br/><br/> <b>Key Responsibilities : </b><br/><br/> - Design and implement end-to-end generative AI solutions including RAG chatbots, LLM-powered BI systems, and coding agents.<br/><br/> - Develop and deploy AI agents using frameworks like LangGraph and similar orchestration tools.<br/><br/> - Build robust data processing pipelines using LlamaIndex and related libraries for document ingestion and retrieval.<br/><br/> - Implement and optimize vector databases for semantic search and retrieval systems.<br/><br/> - Integrate multiple LLM providers (OpenAI, Gemini, Anthropic) and evaluate model performance.<br/><br/> - Set up comprehensive observability and monitoring using tools like LangSmith.<br/><br/> - Collaborate with engineering teams to productionize ML models and AI applications.<br/><br/> <b>Required Skills : Generative AI (Minimum Requirements) : </b><br/><br/> - Hands-on experience with LangGraph or similar AI agent frameworks.<br/><br/> - Proficiency with LlamaIndex, LangChain, or equivalent data processing libraries.<br/><br/> - Experience with vector databases (Pinecone, Weaviate, Chroma, etc.<br/><br/> - Working knowledge of multiple LLMs and their APIs (OpenAI GPT, Gemini, Claude).<br/><br/> - Experience with LLM observability tools (LangSmith, Weights & Biases, etc.<br/><br/> - Proven track record in building LLM BI solutions (natural language to SQL).<br/><br/> - Experience developing RAG (Retrieval-Augmented Generation) chatbots.<br/><br/> - Experience with coding agents and code generation systems.<br/><br/> <b>Traditional AI/ML : </b><br/><br/> - Strong foundation in clustering, regression, classification, and forecasting.<br/><br/> - Proficiency with scikit-learn, PyTorch, TensorFlow.<br/><br/> - Experience with statistical analysis and experimental design.<br/><br/> - Knowledge of feature engineering and data preprocessing techniques.<br/><br/> <b>Good to Have : </b><br/><br/> - Fine-tuning experience with LLMs, rerankers, or embedding models.<br/><br/> - Self-hosting and deployment of open-source LLMs.<br/><br/> - Experience with BERT, transformer architectures, or computer vision models (YOLO).<br/><br/> - MLOps experience with MLflow, Weights & Biases, or TensorBoard.<br/><br/> - Cloud platform certifications (AWS, GCP, Azure).<br/><br/> <b>Additional Requirements : </b><br/><br/> - Strong programming skills in Python.<br/><br/> - Experience with containerization (Docker, Kubernetes).<br/><br/> - Knowledge of API development and microservices architecture.<br/><br/> - Understanding of prompt engineering and prompt optimization techniques.<br/><br/> - Experience with evaluation frameworks for LLM applications.<br/><br/> - Familiarity with data privacy and security best practices for AI applications.<br/><br/> <b>About Us : </b><br/><br/> Grid Dynamics (Nasdaq : GDYN) is a digital-native technology services provider that accelerates growth and bolsters competitive advantage for Fortune 1000 companies.<br/><br/> Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization.<br/><br/> Grid Dynamics achieves high speed-to-market, quality, and efficiency by using technology accelerators, an agile delivery culture, and its pool of global engineering talent.<br/><br/> Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the US, UK, Netherlands, Mexico, India, Central and Eastern Europe.<br/></p><br/></p> (ref:hirist.tech)

Required Skill Profession

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