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As an AI Team Lead, you will be responsible for designing, developing, and deploying AI-powered solutions using modern machine learning and Large Language Model (LLM) technologies. You will lead a team of AI engineers and collaborate with cross-functional stakeholders to build scalable, production-grade AI systems such as chatbots, AI assistants, and intelligent automation solutions. You will utilize your expertise in Python, backend development, LLM integration, and AI system design to deliver impactful solutions aligned with business needs.
Job Responsibility:
Lead and mentor a team of AI/ML engineers, driving technical excellence and delivery
Design and develop AI-powered applications using LLM APIs (OpenAI, Claude, Gemini, etc.)
Build and optimize Retrieval-Augmented Generation (RAG) systems including Agentic RAG architectures leveraging vector databases and semantic search functionalities
Develop scalable backend services and APIs (FastAPI, Flask, etc.) to integrate AI models into products
Implement prompt engineering techniques to improve accuracy, reliability, and performance of AI systems
Design and develop AI-driven solutions such as chatbots, virtual assistants, and document processing systems
(Preferred) Build agentic AI systems with multi-step workflows, tool usage, and autonomous decision-making
Collaborate with data engineers and ML engineers to design end-to-end AI/ML solutions
Ensure production deployment, monitoring, and performance optimization of AI systems
Drive best practices in code quality, architecture, and system scalability
Communicate technical solutions and insights effectively to both technical and non-technical stakeholders
Stay updated with the latest advancements in AI/ML, LLMs, and agentic AI frameworks
Requirements:
Bachelor's or master's degree in computer science, AI, Data Science, or related field
7+ years of relevant experience in AI, machine learning, or software engineering
Strong proficiency in Python and backend development
Hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.)
Experience building AI applications such as chatbots, RAG systems, or AI assistants (using Langchain, Langgraph, CrewAI)
Strong understanding of APIs, system integration, and scalable architecture
Experience with vector databases (Pinecone, FAISS, Weaviate, pgvector, etc.)
Knowledge of prompt engineering and LLM evaluation techniques
Experience deploying AI solutions into production environments
Strong analytical, problem-solving, and communication skills
Ability to lead teams and collaborate cross-functionally