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Urgent Gen Ai Engineer 2 Yrs Immediate 30 Days Preferred

💼 Full-time🗓 2026-07-31

Core

Design, develop, and deploy AI-driven applications leveraging LLMs, Vector Databases, and GenAI frameworks to solve complex real-world problems.

Role type

Gen AI Engineer (Agentic AI)

Builds

AI-driven applications, scalable GenAI-powered APIs, RAG-based solutions

Domain

Generative AI, Agentic AI, Hyper-automation

Deliverable

production ML models | product features

Required skills

Agentic AI development, LangChain, LangGraph, Vector Databases, LLMs, Machine Learning algorithms, Python, FastAPI, TensorFlow, PyTorch, scikit-learn, Keras, SQL, data preprocessing, feature engineering

Preferred skills

AI Ops tools, LLM fine-tuning, eRAG, prompt engineering, NFRs, solution architecture

Technologies

LangChain, LangGraph, FAISS, Pinecone, Weaviate, MongoDB, OpenAI, Azure OpenAI, Anthropic Claude, Meta Llama, FastAPI, TensorFlow, PyTorch, scikit-learn, Keras, LangFuse, Docker, Jenkins, Groovy

Responsibilities

Design and implement Agentic AI workflows, Develop scalable GenAI-powered APIs and microservices, Design and implement RAG-based solutions, Collaborate with cross-functional teams to deliver production-grade GenAI solutions, Apply AI Ops practices for deployment and monitoring, Build and optimize Machine Learning/Deep Learning models

Rewrite
## About Senzcraft Founded by IIM Bangalore and IEST Shibpur Alumni, Senzcraft is a hyper-automation company. Senzcraft vision is to Radically Simplify Today's Work. And Design Business Process For The Future. Using intelligent process automation technologies. We have a suite of SaaS products and services, partnering with automation product companies. Please visit our website - https://www.senzcraft.com for more details Our AI Operations SaaS platform – https://MagicOps.ai Senzcraft on linkedin -> https://www.linkedin.com/company/senzcraft Senzcraft is awarded by Analytics India Magazine in it's report "State of AI in India" as a "Niche AI startup". Senzcraft is also recognized by NY based SSON as a top hyper-automation solutions provider. ## About the Role (Gen AI Engineer) We are seeking a GenAI Engineer with 2+ years of experience and with strong expertise in Agentic AI development using LangChain and LangGraph, along with solid foundations in traditional Machine Learning and Deep Learning. The ideal candidate will own and lead team to design, develop, and deploy AI-driven applications leveraging LLMs, Vector Databases, and GenAI frameworks to solve complex real-world problems. ## Key Responsibilities - Design and implement Agentic AI workflows using LangChain and LangGraph for intelligent automation and reasoning-based solutions. - Develop scalable GenAI-powered APIs and microservices using Python and FastAPI. - Design and implement RAG-based solutions for client. - Collaborate with cross-functional teams to deliver production-grade GenAI solutions with high performance and reliability. - Apply AI Ops practices (LangFuse, Docker, Jenkins, Groovy) for deployment, monitoring, and CI/CD. - Build and optimize Machine Learning/Deep Learning models, understanding on hyperparameter tuning/ performance evaluation. - Stay current with emerging AI trends, frameworks, and best practices in Agentic and Generative AI systems. ## Required Skills & Experience - 2+ years of professional experience in AI/ML or GenAI development. - Hands-on experience with LangChain and LangGraph for Agentic solution design. - Experience working with Vector Databases (FAISS, Pinecone, Weaviate, or MongoDB). - Familiarity with LLMs (OpenAI, Azure OpenAI, Anthropic Claude, Meta Llama, etc.). - Deep understanding of Machine Learning algorithms – regression, decision trees, SVM, random forests, deep learning, and reinforcement learning. - Strong proficiency in Python and FastAPI. - Expertise with frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras. - Strong foundation in mathematics and statistics (linear algebra, calculus, probability, and statistics). - Experience in SQL, data preprocessing, and feature engineering. ## Good to Have - Working knowledge of AI Ops tools – LangFuse, Jenkins, Docker, Groovy, FitNesse, and CI/CD pipelines. - Experience in LLM fine-tuning. - Exposure to eRAG (Azure-based RAG solution). - Familiarity with prompt engineering and LLM observability tools. - Understanding on NFRs, solution architecture and deployment models
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