Generative AI Engineer

Software Developer Key Responsibilities Design, develop, and deployAI/ML solutions with a focus on Generative AI and LLMs . Fine-tune, prompt-engineer, and optimize LLMs for domain-specific tasks. Leverage frameworks such asLangChain, LlamaIndex, or similarfor building modular AI applications. Integrate LLMs with APIs, databases, vector stores, and enterprise applications. Evaluate and implementmodel 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 inAI, ML, and GenAI researchand propose adoption of new technologies. ImplementMLOps best practicesfor continuous training, deployment, and monitoring of models in production. Ensureresponsible AI practices , focusing on bias mitigation, data privacy, and compliance. Required Qualifications 5+ years of experiencein software development (Python preferred; familiarity with Java, C#, or Node.js a plus). 2+ years of hands-on experiencein Generative AI and LLM-based development. Strong knowledge ofAI/ML fundamentalsincluding NLP, deep learning, embeddings, and transformers. Experience withLLMs(e.g., OpenAI GPT, Anthropic Claude, LLaMA, Falcon, Mistral, or similar). Proven track record of deliveringat least 2 production-grade LLM-based projects . Experience withLangChain, LlamaIndex, Haystack, or similar frameworks . Familiarity withvector databases(Pinecone, Weaviate, Milvus, FAISS, Chroma). Hands-on experience withcloud platforms(AWS, Azure, GCP) and AI services (Bedrock, VertexAI, Azure OpenAI). Proficiency incontainerization and deployment tools(Docker, Kubernetes, CI/CD pipelines). Experience withMLOps tools(MLflow, Kubeflow, Weights & Biases) for model lifecycle management. Strong problem-solving, analytical, and communication skills.

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