Technical Lead
10 hours ago
Job Description Key Responsibilities - Technical Leadership - Lead design, architecture, and development of AI-driven applications using GenAI and Agentic AI frameworks. - Mentor and guide a team of developers, ensuring high-quality code and best practices. - Collaborate with product managers, data scientists, and stakeholders to define technical roadmaps. - AI/ML Development - Design, develop, and implement ML/DL models for predictive analytics, NLP, computer vision, and generative AI use cases. - AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers - Build and integrate LLMs, GenAI models, and agent-based AI workflows into enterprise solutions. - Fine-tune, prompt-engineer, and optimize LLMs (OpenAI, Anthropic, Llama, etc.) for business use cases. - Design and implement multi-agent orchestration systems for intelligent automation. - Fullstack Development - Develop scalable web applications using React.js / Angular / Vue.js (frontend) and Python (Django / Flask / FastAPI / Node.js) (backend). - Integrate AI/ML APIs, microservices, and databases (SQL & NoSQL). - Ensure security, scalability, and performance of deployed applications. - Cloud & MLOps - Deploy and manage AI applications on AWS / Azure / GCP. - Implement CI/CD, containerization (Docker, Kubernetes), and model deployment pipelines. - Monitor and optimize model performance in production. Required Skills & Experience - 68 years of experience in Fullstack Development & AI/ML Engineering. - Strong expertise in Python and one backend framework (Flask, FastAPI, Django). - Hands-on experience with GenAI frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.). - Experience in Agentic AI development (multi-agent orchestration, reasoning engines, autonomous agents). - Proficiency in Frontend frameworks (React.js preferred). - Strong knowledge of databases (MySQL, MongoDB, PostgreSQL). - Cloud deployment experience (AWS, Azure, or GCP). - Familiarity with vector databases (Pinecone, Weaviate, FAISS, ChromaDB). - Experience with APIs, microservices, and event-driven architectures. - Proven experience in leading teams, code reviews, and technical decision-making.
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