Generative AI Engineer

Gen AI Developer
Experience: 5 - 9 Years
Immediate Joiners
Preferred skills:
Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy)
GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic Kernel
Machine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch
Key Responsibilities:
Develop scalable Python applications focused on GenAI
Knowledge of Snowflake Cortex is a big plus.
Learn and apply techniques like document chunking and embeddings
Proficient 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 needs
Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
Work 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 functionalities
Deploy, 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 management
Follow coding best practices and contribute to testing and documentation
Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
Communicate effectively with both technical and non-technical team members, ensuring alignment and understanding across all project phases.

Work arrangement
Hybrid