AI ML Lead Engineer

Technology Lead – 8+ yr of exp with 3+ yr of AI/ML relevant experience – Bengaluru/Hyderabad - Hybrid

Roles & Responsibilities:

· Design and develop cutting-edge AI and ML solutions that address business challenges.

· Lead end-to-end AI development lifecycle, from problem definition, data collection to model

deployment and maintenance.

· Collaborate with cross-functional teams to understand and analyze business requirements and

translate them into AI solutions.

· Research and stay up to date with the latest AI and ML technologies and best practices.

· Mentor and provide guidance to junior AI developers on the team.

· Conduct code reviews and ensure code quality, scalability, and performance of AI applications.

· Collaborate with data scientists and engineers to preprocess and prepare data for AI models.

· Evaluate and select appropriate AI and ML algorithms for specific tasks.

· Develop and deploy AI models in a production environment and monitor their performance.

· Ensure data privacy and security measures are implemented in AI solutions.

Requirements / Qualifications

· Education: Bachelor's or master’s in computer science, Data Science, AI, or related field.

· Experience: 8+ years of overall IT experience with at least 3+ years in AI/ML, GenAI, or LLM-based

solution development.

· Programming: Strong skills in Python (Java or similar is a plus).

Generative AI Skills:

· Large Language Models (LLMs) and prompt engineering.

· RAG (Retrieval-Augmented Generation) pipelines design and optimization.

· Integration with Vector Databases (e.g., Pinecone, Weaviate, FAISS, Milvus).

· Agentic frameworks such as LangChain, LangGraph, LlamaIndex, and other orchestration tools.

· Chunking strategies & embeddings optimization for knowledge-intensive applications.

· Chatbot development, conversational AI, and enterprise Q&A assistants.

· Text-to-SQL models, natural language querying over structured/unstructured data.

· PDF/document data extraction pipelines and advanced context retrieval.

· Advanced RAG techniques (e.g., query rewriting, multi-vector retrieval, reranking).

· Fine-tuning, prompt-tuning, or parameter-efficient tuning of LLMs.

Web/UI basics:

· Knowledge of HTML, CSS, or React components for simple UI design to integrate GenAI applications.

· Experience with Flask or FastAPI for building and deploying AI/ML microservices & APIs.

· Data Processing: Pandas, NumPy for preprocessing and manipulation.

· Visualization: Matplotlib, Seaborn (for insights/debugging AI workflows).

· Databases: SQL & NoSQL; expertise in integrating LLMs with enterprise knowledge bases.

· Version Control: Git and collaborative code workflows.

GenAI/AI

· Strong programmatic and architectural skills for building scalable, production-ready GenAI

applications.

· Ability to evaluate, benchmark, and integrate open-source and API-based LLMs (OpenAI, Anthropic, Cohere, LLaMA, Mistral, etc.). · Excellent problem-solving, solutioning, and debugging abilities in fast-paced, evolving AI environments. · Strong communication and leadership skills for guiding teams and partnering with business stakeholders.

Nice to have: