Lead AI Software Architect

7 days ago

vellore, India beBeeArtificialIntelligence Full time

Job Title: AI Lead EngineerAbout This RoleWe are seeking a highly skilled and experienced AI Lead Engineer to lead the design, development, and deployment of cutting-edge artificial intelligence solutions.Key ResponsibilitiesFamiliarize yourself with all AI/ML products, tools, and platforms used within the organization.Lead the design and development of scalable algorithms and machine learning models.Develop and execute technical strategies and roadmaps aligned with business objectives.Build, train, test, and optimize ML and deep learning models for various use cases.Identify, qualify, and propose AI/ML solutions to solve business challenges.Collaborate with product managers, engineers, and stakeholders for requirement gathering and solution delivery.Conduct research on emerging AI techniques and integrate relevant advancements.Oversee deployment, monitoring, and performance tuning of models in production.Provide mentorship to junior engineers and enforce technical best practices.Maintain documentation related to models, datasets, architectures, and workflow processes.Provide regular progress updates to the leadership team.RequirementsMinimum of 5+ years of experience in AI/ML engineering, data science, or algorithm development.Strong experience in machine learning, deep learning, NLP, or computer vision.Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, and scikit-learn.Experience with cloud platforms (AWS/GCP/Azure) and MLOps tools (Docker, Kubernetes, MLflow).Solid understanding of algorithms, data structures, statistics, and optimization techniques.Excellent written and verbal communication skills.Strong problem-solving, analytical, and leadership capabilities.Degree in Computer Science, Data Science, AI/ML, Engineering, or a related field.PREFERRED SKILLSExperience with Generative AI and Large Language Models (LLMs), including fine-tuning, evaluation, and deployment.Knowledge of prompt engineering and agentic workflows.Familiarity with GenAI frameworks such as LangChain, LangGraph, LlamaIndex, Langfuse, CrewAI.Understanding of RAG pipelines and vector databases such as Pinecone, FAISS, Chroma, OpenSearch.Exposure to model optimization techniques like quantization (INT4/GPTQ) and inference acceleration.

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