AI Engineer

ZingMind Technologies; Bengaluru; Hybrid; INR 3,500,000 - 7,000,000; Full time

Job summary

ZingMind Technologies in Bengaluru is seeking an experienced AI/ML Engineer to design and implement end-to-end ML pipelines, focusing on agent-based systems and LangChain integrations.

You will mentor junior engineers, collaborate with client teams, and ensure scalable, low-latency inference using TensorFlow and PyTorch while building memory and tool-use capabilities.

Qualifications

• Total 8+ years of experience in ML/AI system design.
• Experience with agent frameworks and language models.
• Strong Python engineering (async, APIs, microservices).

Responsibilities

• Architect end-to-end ML pipelines for scalable, maintainable models.
• Develop and fine-tune LLMs and Generative AI apps using LangChain.
• Integrate CV and NLP models into existing software to improve UX.
• Optimize inference performance with TensorFlow and PyTorch for production.
• Mentor engineers and conduct rigorous code reviews.

Skills

Python

LangChain

LangGraph

AIOps/MLOps

Tools

Snowflake

Databricks

Job description

Description

Work Locations: Only Bangalore

Experience (Relevant): 8+ Years

Shift Timings: 11AM to 8PM IST

Remote / Hybrid: Hybrid, 3 Days in Client Office Bangalore

Start date: Immediate (within 15 Days)

Top 3 Mandatory Skills

• Python
• Agent Frameworks LangChain, LangGraph
• AIOps/MLOps

Total 8+ years of experience, Build agents/components that reason, plan and act.

Skill Set

• Experience with Agent frameworks, LangChain, LangGraph
• Implement guardrails ReAct patterns
• Develop memory and tool-use capabilities (MCP), collaborate with prompt engineers
• AIOps, Build CI/CD pipelines
• Strong Python engineering (async, APIs, microservices)
• Experience with Snowflake, Databricks, Lakehouse architectures

Key Responsibilities

• Architect and implement end-to-end machine learning pipelines to solve high-impact business problems, ensuring models are scalable and maintainable.
• Develop and fine-tune Large Language Models and Generative AI applications using frameworks like LangChain to enhance user interaction and content generation capabilities.
• Collaborate with engineering teams to integrate Computer Vision and NLP models into existing software architectures, improving product functionality and user experience.
• Optimize model performance by leveraging deep learning frameworks such as TensorFlow and PyTorch to ensure high-throughput and low-latency inference in production environments.
• Mentor junior engineers and conduct rigorous code reviews to maintain high standards of technical excellence and best practices across the AI development lifecycle.