Generative AI Engineer

Grid Dynamics; Hyderabad; Sur place; INR 1 800 000 - 3 000 000; Plein temps

Résumé du poste

Grid Dynamics in Hyderabad is seeking a software professional with 3–6 years of software development experience to design and implement AI-powered applications using Python and modern frameworks.

You will work on Generative AI, LLM-based apps, RAG pipelines, and agentic AI architectures, integrating with REST APIs, microservices, and the best practices in software engineering. A strong understanding of LangChain, vector databases, and AI safety principles will help you thrive.

Qualifications

• 3–6 years of software development experience.
• Strong hands-on Python development.
• Solid understanding of Generative AI and LLMs.
• Experience building LLM-based applications.
• Familiarity with LangChain, vector databases, and AI safety.

Connaissances

Python

Generative AI/LLMs

LLM apps

Agentic AI

RAG pipelines

Prompt engineering

REST APIs

Git & CI/CD

LLM APIs

Tool calling

AI agents

LangChain

Vector databases

AI safety

Outils

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Description du poste

• 3–6 years of software development experience

Required Skills

• Strong hands-on experience with Python
• Strong understanding of Generative AI and Large Language Models (LLMs)
• Experience developing LLM-based applications
• Good understanding of Agentic AI concepts and AI agent architectures
• Experience with RAG pipelines
• Strong knowledge of Prompt Engineering
• Experience with REST APIs and microservices
• Good understanding of Git, CI/CD, testing, and software engineering practices
• Experience with LLM APIs such as OpenAI / Azure OpenAI / Anthropic / Gemini
• Experience with function/tool calling
• Experience building AI agents capable of performing multi-step tasks
• Knowledge of LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent frameworks
• Understanding of vector databases
• Knowledge of LLM evaluation and observability
• Understanding of AI safety, guardrails, and responsible AI practices