Job
Description
Key Responsibilities Design and deploy Large Language Model (LLM)-based applications and GenAI systems. Work closely with internal teams and client stakeholders to gather requirements and deliver scalable AI solutions. Develop and integrate Retrieval-Augmented Generation (RAG) pipelines. Build, test, and deploy APIs and services that bring AI capabilities into business platforms. Perform model optimization, evaluation, and prompt engineering. Mentor junior team members and review technical deliverables. Ensure security, compliance, and ethical usage of AI models in regulated domains. Collaborate with product, design, and engineering teams to shape AI solutions for enterprise clients. Technical Requirements Must-Have Skills 7-10 years of overall experience in AI/ML, with 2-3 years in Generative AI and LLMs. Strong coding skills in Python; familiarity with PyTorch, TensorFlow, or JAX. Experience with: HuggingFace Transformers, LangChain, and OpenAI/Cohere/Claude APIs. Prompt engineering, fine-tuning, and custom embeddings. Proficiency in developing and deploying APIs using FastAPI or Flask. Experience with Docker and containerized deployment. Cloud exposure: Azure, AWS, or GCP, especially ML services like SageMaker, Vertex AI, or Azure ML. Nice-to-Have Skills Experience with vector databases (FAISS, Pinecone, Weaviate). Knowledge of MLOps pipelines and CI/CD for ML workflows. Understanding of responsible AI practices, hallucination reduction, and bias detection. Previous work experience in finance, audit, regulatory, or consulting sectors. Additional Information Leadership in AI project delivery and solution design. Excellent communication and stakeholder engagement skills. Team player with mentoring abilities and technical decision-making confidence. Adaptability to dynamic project requirements and regulatory constraints. Excellent communication and interpersonal skills. Strong problem-solving and debugging skills. Proactive in delivering quality work within deadlines.
