AI Engineer

CCTECH; Ahmedabad District; On-site; INR 1,500,000 - 2,600,000; Full time

Benefits offered by this job

Dynamic engineering IT org

Transforming product development with)

Job summary

CCTech is seeking an AI Engineer to design, build, and operationalise machine learning and generative AI systems from prototype to production. You will work on model development, LLM-based applications, and data/deployment pipelines to ensure accuracy, scalability, and reliability.

Responsibilities include building production ML solutions, developing RAG pipelines and tool use, tuning models for latency and cost, and packaging them as scalable APIs with MLOps practices.

Qualifications

• Proficiency in Python and ML/DL toolkits are essential.
• Hands-on with LLM APIs, prompt engineering and agent frameworks.
• Experience deploying models with MLflow, monitoring, and versioning.

Responsibilities

• Build, evaluate, and deploy ML/DL models for production.
• Develop LLM-based and agentic apps, including RAG pipelines and tool use.
• Fine-tune and optimise models for accuracy, latency, and cost using PEFT and quantisation.
• Design evaluation frameworks, benchmarks, and guardrails for model quality.
• Build and automate data pipelines for training, inference, and monitoring.
• Package and serve models as scalable APIs with containerisation, CI/CD, and MLOps.
• Stay updated with AI/ML advancements and apply them practically.

Skills

Python

ML/DL frameworks

LLM APIs

Prompt engineering

Agent frameworks

RAG pipelines

Embeddings

Vector databases

APIs - FastAPI

Docker

MLOps

SQL

Cloud platforms

Education

BE/B.Tech

M.Tech

CS/IT/Engineering degree

Certifications in cloud/AI/ML

Tools

LangChain

LangGraph

MCP

FastAPI

Docker

MLflow

PyTorch

TensorFlow

scikit-learn

PGVector

FAISS

Pinecone

Job description

CCTech's mission is to transform human life by the democratization of technology. We are a well established digital transformation company building the applications in the areas of CAD, CFD, Artificial Intelligence, Machine Learning, 3D Webapps, Augmented Reality, Digital Twin, and other enterprise applications.

We have two business divisions: product and consulting.

simulationHub is our flagship product and the manifestation of our vision.Currently, thousands of users use our CFD app in their upfront design process.

Our consulting division, with its partners such as Autodesk Forge, AWS and Azure, is helping the world's leading engineering organizations, many of which are Fortune 500 list of companies, in achieving digital supremacy.

Job Description

The AI Engineer designs, builds, and operationalises machine learning and generative AI systems, taking them from prototype to production. The role covers model development, LLM and agentic application engineering, and the data and deployment pipelines that keep these systems accurate, scalable, and reliable.

Key Responsibilities

• Build, evaluate, and deploy machine learning and deep learning models for production.
• Develop LLM-based and agentic applications, including RAG pipelines and tool use.
• Fine-tune and optimise models for accuracy, latency, and cost using PEFT and quantisation.
• Design evaluation frameworks, benchmarks, and guardrails to safeguard model quality.
• Build and automate data pipelines for training, inference, and model monitoring.
• Package and serve models as scalable APIs with containerisation, CI/CD, and MLOps.
• Stay updated with advancements in AI/ML and apply them to practical use cases.

Requirements

Educational Qualifications

• B.E./B.Tech, M.Tech, B.Sc., M.Sc., MCA, or an equivalent degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, or a related quantitative field.
• Relevant certifications in cloud, AI/ML, or software engineering are a plus.

Skillset

• Strong programming skills in Python.
• Experience with ML/DL frameworks (e.g., scikit-learn, PyTorch, or TensorFlow).
• Hands-on experience with LLM APIs, prompt engineering, and agent frameworks (e.g., LangChain, LangGraph, MCP).
• Working knowledge of RAG, embeddings, and vector databases (e.g., pgvector, FAISS, or Pinecone).
• Experience serving models as APIs (FastAPI, Docker) with MLOps practices (MLflow, model versioning, monitoring).
• Proficiency with SQL and data pipeline tooling for large datasets.
• Experience with at least one cloud platform (AWS, Azure, or GCP).

Soft Skills

• Adaptability in a fast-evolving technology landscape.
• Strong problem-solving ability with a structured, hands-on approach.
• Critical thinking to evaluate trade-offs and validate AI generated outputs.

Benefits

• Opportunity to work with a dynamic and fast-paced engineering IT organization.
• Be part of a company that is passionate about transforming product development with technology.