Generative AI Engineer

Software Developer Key Responsibilities Design, develop, and deploy AI/ML solutions with a focus on Generative AI and LLMs . Fine-tune, prompt-engineer, and optimize LLMs for domain-specific tasks. Leverage frameworks such as LangChain, LlamaIndex, or similar for building modular AI applications. Integrate LLMs with APIs, databases, vector stores, and enterprise applications. Evaluate and implement model deployment strategies (on-prem, cloud, serverless, or containerized environments). Collaborate with cross-functional teams (data engineers, product managers, software engineers) to deliver end-to-end AI solutions. Stay updated with the latest advancements in AI, ML, and GenAI research and propose adoption of new technologies. Implement MLOps best practices for continuous training, deployment, and monitoring of models in production. Ensure responsible AI practices , focusing on bias mitigation, data privacy, and compliance. Required Qualifications 5+ years of experience in software development (Python preferred; familiarity with Java, C#, or Node.js a plus). 2+ years of hands-on experience in Generative AI and LLM-based development. Strong knowledge of AI/ML fundamentals including NLP, deep learning, embeddings, and transformers. Experience with LLMs (e.g., OpenAI GPT, Anthropic Claude, LLaMA, Falcon, Mistral, or similar). Proven track record of delivering at least 2 production-grade LLM-based projects . Experience with LangChain, LlamaIndex, Haystack, or similar frameworks . Familiarity with vector databases (Pinecone, Weaviate, Milvus, FAISS, Chroma). Hands-on experience with cloud platforms (AWS, Azure, GCP) and AI services (Bedrock, VertexAI, Azure OpenAI). Proficiency in containerization and deployment tools (Docker, Kubernetes, CI/CD pipelines). Experience with MLOps tools (MLflow, Kubeflow, Weights & Biases) for model lifecycle management. Strong problem-solving, analytical, and communication skills.

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