AI Engineer

Job Title

AI Engineer

Company

None

About Company

Not provided

Location

Pune

Work Mode

ONSITE

Role Overview

The AI Engineer role within the Engineering department is based in Pune and operates on an onsite work mode. Working onsite in Pune enables real‑time collaboration, immediate feedback loops, and hands‑on access to hardware resources necessary for training large models. The primary focus of this position is to design and train machine learning, deep learning, and generative artificial intelligence models that meet the specific requirements of the organization. The engineer will select appropriate algorithms, fine‑tune models for targeted use cases, and ensure that each model aligns with performance expectations. Building end‑to‑end AI applications forms a core part of the responsibilities, including the development of retrieval‑augmented generation (RAG) pipelines and the orchestration of agent workflows that combine multiple AI components into cohesive solutions. The candidate will apply expertise in Python to implement model architectures, preprocess data, and construct training pipelines. Mastery of machine learning concepts enables the selection of suitable techniques, while deep learning knowledge supports the creation of complex neural networks for tasks such as image, speech, or text processing. Familiarity with large language models (LLM) allows the engineer to leverage pre‑trained language capabilities and adapt them through fine‑tuning to address domain‑specific challenges. The role also requires the integration of AI agents using frameworks such as LangChain and LangGraph, facilitating the construction of conversational or decision‑making agents that can interact with external tools or data sources. Orchestration frameworks are employed to manage the sequencing, scaling, and monitoring of these AI components, ensuring reliable operation in production environments. Throughout the development lifecycle, the AI Engineer will evaluate model performance, iterate on hyperparameters, and apply best practices for model validation and testing. Collaboration with cross‑functional teams, including product managers and software engineers, is essential to translate business requirements into technical specifications and to embed AI functionality within larger software systems. The position demands a proactive approach to staying current with emerging AI research and technologies, while applying this knowledge to improve existing solutions. A Bachelor of Technology (B.Tech) degree fulfills the educational requirement for this role, providing a solid foundation in engineering principles that support advanced AI development. Pune’s technology ecosystem provides a supportive environment for AI research and development, and the onsite setting offers direct interaction with teammates and immediate access to resources, fostering an environment where rapid prototyping, iterative testing, and continuous integration of AI models can be efficiently executed. By combining strong programming skills, deep expertise in machine learning and deep learning, and practical experience with LLMs, AI agents, and orchestration tools, the AI Engineer will drive the creation of innovative AI‑driven products and services that enhance the organization’s capabilities.

Key Responsibilities

• Design and develop machine learning models tailored to specific business problems.
• Train deep learning architectures using large and diverse datasets.
• Implement generative AI models for content creation and synthesis.
• Select and evaluate appropriate algorithms for each use case.
• Fine‑tune pre‑trained models to improve performance on targeted tasks.
• Optimize model hyperparameters and monitor performance metrics.
• Build end‑to‑end AI applications that incorporate retrieval‑augmented generation pipelines.
• Develop agent workflows that orchestrate multiple AI components into cohesive solutions.
• Deploy AI solutions within production environments and ensure scalability.
• Collaborate with cross‑functional teams to integrate AI features into larger software systems.

Skills Taxonomy

• Proficient in Python for developing AI solutions.
• Experienced in applying machine learning techniques to solve complex problems.
• Skilled in designing and training deep learning models.
• Knowledgeable about large language models (LLM) and their adaptation.
• Capable of building and managing AI agents for automated tasks.
• Familiar with LangChain for constructing language model pipelines.
• Experienced with LangGraph for graph‑based AI workflow orchestration.
• Competent in using orchestration frameworks to coordinate AI components.

Professional Experience

• Not provided

Education

• A Bachelor of Technology (B.Tech) degree is required.