AI Lead

Njoyn ID - J0726-1020

Location - Hyderabad, Bangalore

Experience -10+Years

Budget - Upto 32 LPA

Notice Period - Only immediate joiners

Key Responsibilities

Lead the architecture, design, development, and deployment of AI-powered applications using Python. Design and develop scalable REST APIs, microservices, and backend systems. Drive the implementation of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agent-based solutions. Develop and optimize AI/ML pipelines, model integrations, and inference workflows. Work with frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent AI orchestration tools. Design and implement vector database integrations, semantic search, embeddings, and knowledge retrieval solutions. Lead cloud-based AI solution development using AWS, Azure, or GCP. Establish coding standards, design principles, testing practices, and code review processes. Implement CI/CD pipelines, containerization, and deployment practices using Docker and Kubernetes. Ensure AI application security, scalability, performance, reliability, and governance. Mentor developers, conduct technical reviews, and drive engineering best practices. Collaborate with product owners, business stakeholders, and cross-functional teams to deliver AI solutions aligned with business objectives. Required Qualifications

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field. 10–15 years of overall software development experience, with substantial experience in Python-based application development. Proven experience in technical leadership, solution architecture, and enterprise application delivery. Hands-on experience building and deploying production-grade AI/ML or Generative AI applications. Strong understanding of software engineering principles, distributed systems, microservices, and cloud-native architectures. Must-Have Skills

Python: Advanced Python programming, OOP, asynchronous programming, error handling, and performance optimization. AI/ML: Machine learning fundamentals, model integration, inference pipelines, and AI application development. Generative AI & LLMs: LLM integration, prompt engineering, embeddings, RAG, and LLM evaluation. AI Frameworks: Experience with frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent. API Development: REST APIs, FastAPI or Flask, microservices, and API integrations. Databases: Strong SQL and experience with relational and NoSQL databases. Cloud Platforms: Hands-on experience with AWS, Azure, or GCP. Vector Databases: Experience with vector search and databases such as Pinecone, Weaviate, Chroma, or FAISS. DevOps & Deployment: Git, CI/CD, Docker, Kubernetes, and production deployment practices. Leadership: Technical ownership, architecture decisions, code reviews, mentoring, and stakeholder management. Good-to-Have Skills

Experience building Agentic AI applications and multi-agent orchestration workflows. Familiarity with Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication. Experience with AI evaluation frameworks, hallucination detection, guardrails, and responsible AI practices. Knowledge of fine-tuning, model optimization, quantization, and open-source LLMs. Experience with cloud AI services such as AWS Bedrock, Azure OpenAI, or Google Vertex AI. Familiarity with MLflow, Kubeflow, model monitoring, and MLOps practices. Experience with event-driven architectures, Kafka, and distributed processing. Knowledge of AI security, prompt injection prevention, access control, and data privacy. Experience with observability tools, logging, tracing, and monitoring for AI applications. Preferred Candidate Profile

Strong problem-solving and analytical skills. Ability to balance hands-on development with technical leadership. Excellent communication and stakeholder management skills. Experience delivering scalable, production-ready AI solutions in an enterprise environment. Ability to drive innovation, evaluate emerging AI technologies, and translate them into business value.