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Senior GenAI Engineer

Weekday
Remote, IND
Full-time
Senior · 6+ years experience
Remote
Discovered 2 days ago
awsazuredockergcpkuberneteslangchain

Full Job Posting

Key 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

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
  • 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 Qualifications:

  • 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
  • Must-have skills
  • Agentic AI, Generative AI, Artificial Intelligence
  • Good-to-have skills
  • Machine Learning, LangChain, LangGraph

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