AI Developer / Generative AI Engineer

Cognizant

13 days ago

Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Languages

English

Job location

Tech stack

API

Artificial Intelligence

Data analysis

Artificial Neural Networks

Azure

Big Data

Cloud Computing

Computer Programming

Databases

Information Engineering

ETL

Data Mining

Software Design Patterns

Python

Machine Learning

Neo4j

Azure

Software Engineering

SQL Databases

Azure

Large Language Models

Multi-Agent Systems

Prompt Engineering

Deep Learning

Generative AI

Gitlab

Data Analytics

REST

GPT

Software Version Control

Data Pipelines

Databricks

Job description

Design, develop, and deploy AI solutions leveraging Generative AI, LLMs, and multi-agent architectures.
Build data pipelines, perform data preprocessing, and manage data transformations using SQL and other tools.
Apply machine learning and deep learning techniques such as classification, clustering, and predictive modeling.
Develop and integrate RAG (Retrieval-Augmented Generation) systems, prompt engineering, and vector database implementations.
Collaborate with cross-functional teams to design scalable AI workflows and orchestration systems.
Implement and maintain CI/CD pipelines, API integrations, and version control systems.
Contribute to optimization of data analytics, model performance, and AI infrastructure.

Requirements

Do you have experience in SQL?, Do you have a Master's degree?, We are seeking experienced AI Developers with strong expertise in Python and hands-on experience building and deploying Generative AI solutions using LLMs, LangGraph, Neo4j, and multi-agent orchestration frameworks (MCP/A2A protocols). The ideal candidate should also have a solid foundation in traditional machine learning, data engineering, and cloud-based AI workflows., * Programming Proficiency:

Strong expertise in Python for AI/ML development.
Proficiency with SQL, ETL design patterns, and data modeling techniques.
Generative AI & LLM Development:
Hands-on experience with GPT-based models, LangChain, LangGraph, and vector databases.
Experience with RAG architectures and prompt engineering.
Knowledge of multi-agent systems, AI orchestration, and MCP/A2A protocols.
Machine Learning Expertise:
Solid foundation in classification, clustering, regression, decision trees, and neural networks.
Experience in predictive modeling and data mining.
Data Engineering & Analytics:
Experience in data preprocessing, transformation, and pipeline development.
Strong analytical skills with ability to work with large datasets.
Software Engineering Practices:
Familiarity with APIs, RESTful web services, and data connectors.
Experience with GitLab (or similar version control systems) and CI/CD pipelines.