Weekday AI
Agentic AI Engineer
- India · Remote
- Full-time
- Posted
Skills
Job 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.
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