LLMOps Engineer

2 days ago

Mumbai City District, India Lenden Club Techserve Full time ₹ 12,00,000 - ₹ 36,00,000 per year

About LenDenClub

LenDenClub is India's largest Peer-to-Peer (P2P) Lending platform, owned and operated by Innofin Solutions Pvt. Ltd., an RBI-registered (NBFC-P2P). It provides an opportunity to lenders looking for high interest rates by connecting them with creditworthy borrowers looking for short-term loans. LenDenClub has become a go-to platform to earn returns, lenders have historically earned an XIRR 11.28% p.a. The platform has an active user base of over 2 Cr+ users and loan disbursal of over 15,000 crores.

Why work at LenDenClub

At LenDenClub, we take pride in being the first Peer-to-Peer lending platform to offer ESOP liquidity, and this achievement has allowed us to set a new benchmark. The progressive approach towards employee benefits has been acknowledged and appreciated and as a result, LenDenClub has been certified as a 'Great Place to Work' successively for four years by the Great Place to Work Institute, Inc. As a LenDenite, you are a part of an enthusiastic and passionate group of individuals who own and love what they do. At LenDenClub, we believe in creating leaders, and you get to work with complete freedom to chase your ultimate career goal without any inhibitions. We remain committed to continuing our journey of innovation and fostering a positive work environment for our team.

Position: LLMOps Engineer

Location: Malad, Mumbai

Work Mode: Work from office, 6 days/week (alternate Saturdays off)

We are looking for a seasoned LLMOps Engineer to design, deploy and optimize enterprise-grade LLM systems with a focus on scale, cost and compliance.

Responsibilities:

  • Manage full LLM lifecycle: data preprocessing, fine-tuning, evaluation, deployment, retraining.
  • Deploy & scale large-weight LLMs with distributed inference, GPU optimization, quantization and caching.
  • Build RAG pipelines with embedding generation, vector DBs (FAISS, Pinecone, Weaviate, Milvus) and retrieval strategies.
  • Implement observability frameworks for latency, token usage, hallucination detection, guardrails, cost tracking.
  • Integrate LLMs with APIs, microservices, and enterprise workflows (LangChain, LlamaIndex, Triton Inference Server).
  • Continuously optimize GPU utilization, inference throughput and cost efficiency.

Requirements:

  • Strong knowledge of LLM deployment, RAG architectures, embeddings, multimodal pipelines.
  • Expertise in AWS GPU infra (EKS, Inferentia, Trainium), caching and distributed inference.
  • Experience with monitoring frameworks.
  • Proven track record of scaling enterprise LLM applications with compliance & observability frameworks.

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