AI Engineer

Job Description Job Title: AI Engineer

About The Role We are seeking a skilled AI Engineer to design, develop, and deploy intelligent AI solutions that solve complex business problems and improve product capabilities. The ideal candidate will be responsible for developing, training, testing, and optimizing machine learning and artificial intelligence models, integrating AI capabilities into applications, and supporting AI solutions throughout the development lifecycle. The role involves working closely with data scientists, software engineers, product managers, and business stakeholders to understand requirements and deliver scalable, reliable, and production-ready AI applications.

We are seeking a detail-oriented and results-driven AI Engineer for a W2 - Full Time engagement, offering a Onsite / Hybrid / Remote (Based on Business Requirements) work arrangement. The ideal candidate brings 3 – 7 years of hands-on experience and is proficient in industry-leading tools and technologies such as Python, Machine Learning, Deep Learning, Generative AI and 5 more . Strong domain knowledge in key practices including data preprocessing, model performance optimization, deployment, monitoring, troubleshooting AI systems and more is essential for this role. This role requires strong ability to collaborate with cross-functional teams, identify defects early in the development cycle, and ensure high-quality product delivery.

Job Classification: W2 - Full Time

Work Mode: Onsite / Hybrid / Remote (Based on Business Requirements)

Experience Required: 3 – 7 years

Primary Skills

• Python
• Machine Learning
• Deep Learning
• Generative AI
• Natural Language Processing
• Computer Vision
• TensorFlow
• PyTorch
• Scikit-learn

Secondary Skills

• data preprocessing
• model performance optimization
• deployment
• monitoring
• troubleshooting AI systems
• Agile

Soft Skills

• analytical
• problem-solving
• programming
• communication
• collaboration

Nice to Have

• Experience with Large Language Models
• Retrieval-Augmented Generation
• prompt engineering
• vector databases
• LangChain
• REST APIs
• AI model evaluation
• Knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud
• Docker
• Kubernetes
• Git
• CI/CD
• MLOps practices