jobapplier

Lead AI Engineer

LeadSquared

This job is closed: the employer no longer lists it.

Skills

Required

  • AI
  • NumPy
  • Pandas
  • FastAPI
  • async
  • SQL
  • OpenAI
  • Anthropic Claude
  • Gemini
  • Llama
  • Mistral
  • prompt engineering
  • Pinecone / Weaviate / Qdrant / Milvus / Chroma / FAISS / pgvector
  • PyTorch
  • TensorFlow / Keras

Preferred

  • LlamaIndex, CrewAI / AutoGen
  • Protocol
  • integrations
  • LoRA / QLoRA
  • PEFT
  • RLHF / DPO
  • Text classification
  • NER
  • summarisation
  • OpenCV

Lead AI Engineer 14 Oct 2026 · @Shruti Experience: 4–6 years · Type: Full-time · Location: Bengaluru About the role We are hiring a hands-on

AI Engineer to own our AI stack end to end: generative AI, agentic systems, deep learning, NLP and computer vision. You will set technical direction, lead a small team, and ship AI products that are reliable, safe and measurable in production.

Responsibilities

  • Architect and build GenAI and agentic AI solutions: multi-agent workflows, tool calling, memory and human-in-the-loop.
  • Design, optimise and evaluate RAG pipelines and vector search for accurate, grounded answers.
  • 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 optimise them for quality, cost and latency.
  • Implement guardrails, security and responsible-AI practices (bias, privacy, hallucination and prompt-injection controls).
  • Lead and mentor AI engineers, review code and designs, and partner with product and business teams on use cases and success metrics.

Requirements

  • Expert Python (NumPy, Pandas, FastAPI, async); SQL.
  • OpenAI, Anthropic Claude, Gemini, Llama and Mistral; prompt engineering, structured outputs and function calling.
  • Chunking, embeddings, hybrid search and re-ranking; Pinecone, Weaviate, Qdrant, Milvus, Chroma, FAISS or pgvector.
  • PyTorch and TensorFlow/Keras; CNNs, RNNs and Transformers.
  • Bachelor's or Master's in Computer Science, AI, Data Science or a related field.
  • Nice to have Knowledge graphs or graph RAG, speech AI (ASR/TTS), multimodal models, edge or on-device inference, and open-source contributions or publications.

Preferred

  • LangChain, LangGraph, LlamaIndex, CrewAI or AutoGen; MCP (Model Context Protocol) and tool integrations.
  • Hugging Face Transformers, LoRA/QLoRA, PEFT and RLHF/DPO basics.
  • Text classification, NER, summarisation; OpenCV, YOLO and vision-language models.
  • Ragas or DeepEval, guardrails, bias and safety testing.

Cloud

AWS (SageMaker, Bedrock), Azure (Azure OpenAI, Azure ML) or GCP (Vertex AI).