Agentic AI Engineer

About the job

Position Description Job Title: Agentic AI Engineer Position: Senior Software Engineer / Lead Analyst Experience: 3 - 10 Years Category: Software Development/ Engineering Shift: : General shift Main location: India, Bangalore/ Pune Position ID: J0226-1192 Employment Type: Full Time Education Qualification: Bachelor's degree in Computer Science or related field or higher with minimum 3 years of relevant experience. Your future duties and responsibilities • Strong software development background on Python for 3 or more years • Hands-on experience building applications with AI/ML technologies for 6 months or more, particularly in the domain of conversational AI (chatbots, voice bots). • Experience with Large Language Models (LLMs) and key concepts like prompt engineering, retrieval-augmented generation (RAG), and agentic AI that uses tools. • Practical experience with cloud platforms, preferably Google Cloud Platform (GCP), and its AI/ML services (e.g., Dialogflow CX, Vertex AI). • Proven ability to integrate software systems via APIs and a solid understanding of API design principles. • A passion for creating clean, efficient, and reusable code. • Excellent problem-solving skills and the ability to work effectively in a fast-paced, Agile environment. Required Qualifications To Be Successful In This Role Must Have Skills: • Strong programming skills in Python (mandatory) • Hands-on experience with LLMs and Generative AI concepts • Experience with frameworks like LangChain, LlamaIndex, or similar • Strong understanding of prompt engineering and agent design patterns • Experience in building RAG pipelines (vector databases, embeddings) • Knowledge of REST APIs and system integrations • Familiarity with databases (SQL / NoSQL) • Understanding of cloud platforms (AWS, Azure, or GCP) • Strong problem-solving and system design skills Good to Have Skills: • Experience with multi-agent systems and autonomous workflows • Exposure to tools like OpenAI APIs, Azure OpenAI, or Hugging Face • Experience with vector databases (Pinecone, FAISS, Weaviate, etc.) • Knowledge of MLOps / LLMOps practices (monitoring, evaluation, versioning) • Experience with Docker, Kubernetes, and scalable deployments • Familiarity with real-time streaming and event-driven architectures • Experience in building chatbots or conversational AI systems • Understanding of AI safety, guardrails, and responsible AI practices • Exposure to fine-tuning or model customization.