Job Description
Vacancy for AI Engineer
EY exists to shape the future with confidence, helping to create long-term value for clients, people and society. At EY Sri Lanka, you’ll have the chance to build a career as unique as you are, with the global scale, superb support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. You will be given the opportunity to work and take responsibility in challenging engagements and gain exposure across various sectors.
The Opportunity
When you join as an AI Engineer, you’ll do more than just advise businesses, you’ll collaborate with key decision-makers to help them make better choices. Our team is dedicated to leveraging business expertise and cutting-edge technology to solve complex challenges facing our clients. We are currently expanding our capabilities in AI (including Generative AI technologies and are looking for a skilled AI engineer to join our dynamic team. You will design and implement the intelligence layers of multi-agent systems. You’ll collaborate with team members to build, integrate, and deploy secure, performant AI agents powered by LLMs and Retrieval-Augmented Generation (RAG) architectures.
Key roles and responsibilities:
- Implement AI solutions using various technologies that address client-specific needs and add tangible value.
- Understand the latest AI trends and technologies to ensure EY remains at the forefront of innovation.
- Design, develop, and deploy machine learning and AI models across various use cases (predictive analytics, NLP, computer vision, recommendation systems, LLM-based workflows, etc.).
- Build and maintain scalable model training, evaluation, and inference pipelines.
- Implement best practices around MLOps, including versioning, CI/CD, monitoring, retraining, and automation.
- Integrate AI models into production systems and applications using APIs, microservices, or model-serving platforms.
- Fine-tune and optimize Large Language Models (LLMs) and leverage frameworks like LangChain, RAG (Retrieval-Augmented Generation), prompt engineering strategies, or vector search.
- Collaborate with cross-functional teams to translate business requirements into technical AI solutions.
- Ensure AI solutions meet standards for accuracy, reliability, explainability, and ethical AI practices.
Required skills and experience:
- 5+ years of hands-on experience in AI/ML engineering or applied machine learning roles.
- Strong programming skills in Python (required) and familiarity with AI/ML libraries such as:
- TensorFlow
- PyTorch
- Scikit-learn
- Keras
- XGBoost
- LightGBM
- Deep understanding of machine learning concepts including: feature engineering, model evaluation, hyperparameter tuning, cross-validation, interpretability.
- Experience with modern AI platforms and frameworks, such as:
- Hugging Face, LangChain or similar LLM orchestration frameworks
- Vector databases (Pinecone, Weaviate, FAISS, ChromaDB)
- Hands-on experience with cloud-based ML platforms (one or more):
- Azure ML Studio, Cognitive Services, OpenAI Services
- AWS: SageMaker, Bedrock, Rekognition
- GCP: Vertex AI, BigQuery ML
- Experience monitoring and optimizing cloud resource usage and costs using cost management and performance profiling tools.
- Experience applying MLOps/DevOps practices - including automated testing, CI/CD (Azure DevOps/GitHub Actions), containerization (Docker).
- Familiarity with front-end frameworks (React) for building lightweight user interfaces and integrating seamlessly with AI back-ends.
- Experience with Generative AI applications (NLP, chatbots, multimodal AI, RAG pipelines).
- Knowledge of deep learning architectures (CNNs, RNNs, Transformers).
- Experience with containerization and DevOps tools: Docker, Kubernetes, GitHub Actions, Terraform.
- Familiarity with model governance frameworks and ethical AI compliance.
- Knowledge of experimentation/tracking tools such as: MLflow, Weights & Biases, Neptune.ai.
Educations & Certifications:
- Bachelor’s or master’s degree in AI, Machine Learning, Data Science, IT, Statistics, Engineering, Computer Science, or related fields.
- Relevant certifications such as:
- Azure AI Engineer Associate
- Google Professional Machine Learning Engineer
- AWS Machine Learning – Specialty
- Databricks Machine Learning Professional
- OpenAI, Hugging Face, or Nvidia-based certifications
What working at EY offers:
- Growth and learning opportunities
- Global exposure
- Purpose-led work
How to Apply?
If interested, please submit your resume with the names and contact details of two unrelated referees to [email protected]. Please state 'AI Engineer position' in your application.
All applications must be submitted by December 31, 2025.
