Lead AI Engineer
LeadSquared20 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Architect and build generative AI and agentic AI solutions using multi-agent workflows, tool calling, memory, and human-in-the-loop capabilities.
- Design, optimize, and evaluate RAG pipelines and vector search, including chunking, embeddings, hybrid search, and re-ranking.
- Fine-tune and adapt LLMs and other foundation models for domain-specific tasks.
- Build and deploy deep learning, NLP, and computer vision models for prediction, classification, and automation.
- Evaluate AI systems and optimize them for quality, cost, and latency.
- Implement guardrails, security, and responsible-AI practices covering bias, privacy, hallucinations, and prompt injection.
- Lead and mentor AI engineers, review code and designs, and partner with product and business teams on use cases and success metrics.
Requirements
- 4–6 years of experience.
- Expert Python experience, including NumPy, Pandas, FastAPI, and async programming, plus SQL.
- Experience with generative AI and LLMs, including OpenAI, Anthropic Claude, Gemini, Llama, Mistral, prompt engineering, structured outputs, and function calling.
- Experience with agentic AI frameworks and tools such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, MCP, and tool integrations.
- Experience with RAG, vector databases, embeddings, hybrid search, and re-ranking, using technologies such as Pinecone, Weaviate, Qdrant, Milvus, Chroma, FAISS, or pgvector.
- Knowledge of Hugging Face Transformers, LoRA/QLoRA, PEFT, and RLHF/DPO basics.
- Experience with PyTorch and TensorFlow/Keras and deep learning architectures including CNNs, RNNs, and Transformers.
- Experience with NLP and computer vision tasks such as text classification, NER, summarization, OpenCV, YOLO, and vision-language models.
- Experience with AI evaluation and responsible AI practices, including Ragas or DeepEval, guardrails, bias testing, and safety testing.
- Experience with cloud AI services on AWS, Azure, or GCP.
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
- Nice-to-have experience with knowledge graphs, graph RAG, speech AI such as ASR/TTS, multimodal models, edge or on-device inference, open-source contributions, or publications.
Benefits
- Full-time position located in Bengaluru.