AI Engineer

AI Engineer building and deploying enterprise AI models, LLM agents, and machine-learning solutions at EY. Delivering scalable systems across EY’s global assurance and consulting network.

Posted 9/8/2026full-timeKochi • 🇮🇳 IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing advanced AI models, with a strong focus on prompt engineering, fine-tuning, and deploying scalable AI solutions using cloud platforms. Proficient in MLOps practices and experienced in collaborating with diverse teams to deliver end-to-end AI projects.

Highest-signal resume keywords

AI Model DevelopmentPrompt EngineeringMLOps PracticesCloud DeploymentPython Programming

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML Model Fine-TuningTransformer-Based Deep LearningStatistical MethodsExperimental DesignNoSQL DatabasesSQL DatabasesTensorFlowPyTorchDockerCI/CD Principles

Soft Skills

CollaborationCultural SensitivityAdaptability

Tools & Technologies

AWSGoogle CloudAzureFlaskFastAPIWord2VecNLTKSpaCyBERTLangChain

Industry Keywords

GenAILLMNLPMulti-Agent SystemsRetrieval Augmented Generation

Tech Stack

Tools & technologies

AWSAzureCloudDockerFlaskMongoDBNoSQLPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Design, develop, and implement advanced AI models with minimal supervision
Play an integral role in machine learning projects
Deliver scalable, optimized, enterprise AI solutions end to end
Perform prompt engineering and fine-tuning of AI/ML, GenAI, and LLM models
Build AI agents and multi-agent systems
Fine-tune, transfer-learn, and optimize Transformer-based deep learning models
Deploy models and containers using cloud platforms and Docker
Apply MLOps practices for machine learning CI/CD
Test and debug complex codebases
Collaborate with culturally diverse outsourced, onshore, and offshore team members
Work outside normal working hours when needed
Travel as required

Requirements

What you’ll need

Bachelor's/Master's degree in Computer Science, Engineering, Mathematics, Data Science, or a related technical field
Minimum of 5–7 years' experience
End-to-end delivery of scalable, optimized, enterprise AI solutions
Prompt engineering and fine-tuning of AI/ML, GenAI, and LLM models
Experience building Agents and Multi Agent Systems
Fine-tuning, transfer learning, and optimization of Transformer architecture-based deep learning models
Experience with Agentic AI, GenAI, LLM, and NLP tools including Word2Vec, NLTK, spaCy, BERT, GloVe, AutoGen, LangChain, and LangGraph
Working understanding of AWS, Google Cloud, or Azure
Strong Python programming skills; experience with Flask and FastAPI
Docker experience for container deployment
Experience with NoSQL, SQL, and vector databases
Strong knowledge of statistical methods and experimental design
Experience with MLOps practices for machine learning CI/CD
Solid understanding of supervised and unsupervised learning
TensorFlow, PyTorch, or Scikit-Learn experience
Experience setting up Docker images and using NoSQL databases such as MongoDB
Familiarity with Retrieval Augmented Generation and AI agent platforms
Practical experience in testing methodologies and debugging complex codebases
Understanding of CI/CD principles and tools such as GitHub Actions
Experience deploying models with cloud services, preferably Azure
Hands-on experience developing and deploying LLM-based AI agents
Experience applying risk management concepts within AI and ML applications
Ability to work with culturally diverse outsourced/onshore/offshore teams, potentially outside normal working hours
Some travel may be required

Benefits

Comp & perks

Flexible environment
Future-focused skills development
World-class experiences
Diverse and inclusive culture
Globally connected teams