Job Opening for AI Engineer Fresher (Job Code RT 1612)

Radical Technologies; Pune District; On-site; INR 400,000 - 700,000; Full time

Job summary

Radical Technologies in Pune is seeking an AI Engineer Fresher to join a next-generation team building intelligent systems that combine ML, LLMs, and agentic reasoning. You will participate end-to-end from data ingestion and model training to deployment of scalable microservices.

You will design RAG pipelines, train models with PyTorch/TensorFlow, and integrate with vector databases and LLM APIs, while collaborating with data and backend engineers on production-grade systems.

Qualifications

• Fresher with strong curiosity in AI and agentic systems.
• Analytical mindset with focus on debugging, optimisation, and scalability.
• Strong communication and documentation skills for collaborative workflows.
• Innovative and research-driven approach toward new AI architectures.
• Eagerness to experiment, iterate, and learn from production-level systems.

Responsibilities

• Design and implement RAG pipelines for data retrieval and reasoning.
• Build, train, and fine-tune ML models with Python ML frameworks.
• Develop modular AI microservices with FastAPI/Flask and vector DBs.
• Orchestrate multi-agent systems using LangGraph/LangChain.
• Integrate and evaluate LLM APIs for reasoning and automation.
• Create data/ML pipelines for training, evaluation, and inference.
• Expose REST or WebSocket APIs for model and agent communication.
• Apply prompt engineering and reranking to improve accuracy.
• Collaborate with data/backend/AI engineers to deploy and monitor microservices.

Skills

Python

RAG pipelines

ML/DL frameworks

LLM integration

FastAPI/Flask

LangChain

LangGraph

Vector databases

Docker

REST/WebSocket APIs

Prompt engineering

Airflow/ZenML/Dagster

Tools

FastAPI

Flask

LangGraph

LangChain

MCP

FAISS

ChromaDB

Elasticsearch

TensorFlow

PyTorch

Docker

Git

MLflow

DVC

AWS SageMaker

GCP Vertex AI

Azure ML

Weaviate

REST APIs

Job description

Job Opening for AI Engineer Fresher (Job Code RT 1612)

Pune, Mumbai Full-Time Work from Office 0 to 1 Year (Fresher)

Job Brief

As an AI Engineer, you will be part of a next-generation engineering team building intelligent, autonomous systems that combine Machine Learning, Large Language Models (LLMs), and Agentic reasoning frameworks. You will participate end-to-end — from data ingestion and model training to Retrieval-Augmented Generation (RAG), agent orchestration, and deployment of scalable microservices. This role demands curiosity, precision, and a passion for bridging traditional ML with modern LLM-based agentic architectures in production-grade systems.

Responsibilities

• Design and implement RAG pipelines for large-scale data retrieval and contextual reasoning.
• Build, train, and fine-tune ML models using Scikit-learn, TensorFlow, or PyTorch for structured and unstructured datasets.
• Develop modular AI microservices (FastAPI/Flask) integrated with vector databases (FAISS, ChromaDB, Elasticsearch) and embedding pipelines.
• Orchestrate multi-agent systems using LangGraph, LangChain, or Model Context Protocol (MCP) for dynamic task execution.
• Integrate and evaluate LLM APIs (OpenAI, Azure OpenAI, Groq, Anthropic, etc.) for reasoning, generation, and workflow automation.
• Implement data and ML pipelines (Airflow, ZenML, Dagster) for training, evaluation, and inference.
• Develop and expose REST or WebSocket APIs for model and agent communication.
• Apply prompt engineering and reranking strategies to improve contextual accuracy and system reasoning.
• Work closely with data, backend, and AI engineers to deploy, scale, and monitor intelligent microservices in test/staging environments.
• Contribute to shared AI infrastructure modules, ensuring reproducibility, maintainability, and performance.
• Research and prototype new architectures, including multimodal RAG, structured reasoning, or fine-tuning pipelines.

Requirements

• Curiosity to explore Agentic AI frameworks and autonomous reasoning systems.
• Analytical mindset with a focus on debugging, optimisation, and scalability.
• Strong communication and documentation skills for collaborative workflows.
• Innovative and research-driven approach toward new AI architectures.
• Eagerness to experiment, iterate, and learn from production-level systems

Skills

• Strong understanding of RAG architecture — document chunking, embedding, retrieval, reranking, and synthesis.
• Proficiency in Python, including Pandas, NumPy, and Scikit-learn.
• Experience with FastAPI or Flask for microservice and API development.
• Hands-on experience with LangGraph, LangChain, or MCP for multi-agent orchestration.
• Familiarity with vector databases (FAISS, ChromaDB, Weaviate, Elasticsearch).
• Working knowledge of ML/DL frameworks (TensorFlow, PyTorch).
• Understanding of model serving via REST APIs, batch jobs, or pipelines.
• Exposure to containerisation (Docker) and scalable architecture patterns.
• Familiarity with Git, MLflow, or DVC for versioning, tracking, and collaboration.
• Awareness of cloud AI/ML services (Azure ML, AWS SageMaker, GCP Vertex AI).
• Understanding of prompt evaluation, retrieval accuracy metrics, and contextual reasoning benchmarks.