Generative AI Engineer

Gen AI DeveloperExperience: 5 - 9 YearsImmediate JoinersPreferred skills:Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy)GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic KernelMachine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch

Key Responsibilities

Develop scalable Python applications focused on GenAIKnowledge of Snowflake Cortex is a big plus.Learn and apply techniques like document chunking and embeddingsProficient in both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization.Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needsImplement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineeringLead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systemsUtilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agentsDevelop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time informationLead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiencesWork with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)Design and implement scalable RESTful APIs and microservices to expose AI functionalitiesDeploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle managementFollow coding best practices and contribute to testing and documentationStay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentationCollaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineersCommunicate effectively with both technical and non-technical team members, ensuring alignment and understanding across all project phases.