Senior GenAI Engineer

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.

Requirements

• 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
• 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