AI ENGINEER
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Job Description
Job Summary
The AI Engineer is responsible for designing, developing, and deploying artificial intelligence and machine learning solutions that address business challenges and automate processes. The role builds scalable AI-powered applications by leveraging machine learning, generative AI, data engineering, and cloud technologies while collaborating with cross-functional teams to drive business value.
Responsibilities
The AI Engineer is responsible for designing, developing, and deploying artificial intelligence and machine learning solutions that address business challenges and automate processes. The role builds scalable AI-powered applications by leveraging machine learning, generative AI, data engineering, and cloud technologies while collaborating with cross-functional teams to drive business value.
Responsibilities
- Design, develop, and implement AI and machine learning solutions using modern frameworks and technologies to support business and operational objectives
- Build, train, validate, and optimize machine learning and deep learning models to improve accuracy, performance, and scalability
- Develop and manage data pipelines, data processing workflows, and AI infrastructure to support model training, deployment, and monitoring
- Deploy and integrate AI solutions into enterprise applications using APIs, microservices, and cloud-based platforms
- Collaborate with business stakeholders, data scientists, and technology teams to identify opportunities, solve complex problems, and drive innovation through AI initiatives
- Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field
- At least 5 to 7 years of experience in designing, developing, and implementing AI, machine learning, or data-driven solutions in enterprise environments
- Strong proficiency in Python, machine learning frameworks such as TensorFlow and PyTorch, and AI technologies including generative AI and large language models
- Experience with cloud platforms (AWS, Azure, or Google Cloud), data engineering, MLOps practices, APIs, microservices, and containerized application deployment
- Strong analytical, problem-solving, communication, and collaboration skills; banking or financial services experience is an advantage
More Info
Key Skills
generative AI
large language models
containerized application deployment




