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