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Senior GenAI Engineer

Weekday AI

Responsibilities

  • Architect and build scalable Generative AI and agentic AI applications, end to end
  • Design LLM-powered workflows and prompt strategies for reflexive, self-learning, multi-agent systems
  • Build intelligent AI agents using LangChain and LangGraph for use cases like NL-to-SQL, autonomous task agents, and RAG pipelines

Select, customize, fine-tune, and optimize state-of-the-art LLMs

  • Design and own full ML/GenAI pipelines — training, deployment, monitoring, lifecycle management
  • Build APIs, microservices, and integration frameworks to bring AI into enterprise products
  • Champion responsible AI practices — mitigating hallucinations, bias, and reliability risks
  • Partner directly with customers, product, and engineering to turn business needs into robust AI architecture
  • Mentor engineers and help shape our long-term AI platform strategy

Preferred

  • LLM fine-tuning experience (LoRA, RLHF, PEFT)
  • Performance optimization (GPU/TPU acceleration, quantization, pruning, distillation)

AI observability/monitoring tool experience

  • Familiarity with AI governance and compliance (GDPR, SOC 2)
  • Prior consulting or solution-architecture experience shipping enterprise AI products
  • Background in financial services, healthcare, or insurance
  • Machine Learning, LangChain, LangGraph

Senior GenAI Engineer

Weekday AI · India (Remote) · Full-time · Posted 2026-09-11

Description

  • This role is for one of Weekday’s clients
  • Min Experience: 5+ years
  • Location: Remote (India)

JobType: full-time

We're looking for a Senior Agentic AI/Generative AI Engineer to help architect our next-generation AI-driven products — from prototyping through production deployment. This is a customer-facing role where you'll move fluidly between solution architecture, hands-on engineering, and client conversations.

Required Qualifications

  • 6+ years in traditional ML, including 2+ years hands-on with Generative AI
  • Strong experience with LLMs (GPT and similar), prompt engineering, and agentic systems
  • Real-world experience with LangChain/LangGraph or similar agentic frameworks
  • Strong Python skills — API wrappers, third-party integrations, internal tooling
  • Solid foundation in Transformers, CNNs, RNNs — hands-on with TensorFlow, PyTorch, Scikit-learn

Experience with NLP, embedding models, and vector databases

  • Hands-on work with OpenAI, Llama/Llama2, Azure OpenAI, and other open-source models
  • Experience designing distributed, cloud-native architectures (microservices, REST APIs)

Proficiency with AWS, Azure, or GCP, plus Docker/Kubernetes

  • MLOps/LLMOps experience — training, deployment, monitoring, lifecycle management
  • Excellent communication skills — you can translate technical depth for non-technical stakeholders
  • Bachelor's or Master's in CS, Data Science, Engineering, Math, Statistics, or related field
  • Comfort with startup pace and strong ownership mentality

Must-have skills

Agentic AI, Generative AI, Artificial Intelligence

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