We are seeking a highly skilled and experienced Senior AI Engineer to lead the design, development, and deployment of advanced AI solutions across our enterprise. The ideal candidate will have a deep understanding of AI / ML algorithms, scalable systems, and data engineering best practices.
Responsibilities
- Design and develop production-grade AI and machine learning models for real-world applications (e.g., recommendation engines, NLP, computer vision, forecasting).
- Lead model lifecycle management from experimentation and prototyping to deployment and monitoring.
- Collaborate with cross-functional teams (product, data engineering, MLOps, and business) to define AI-driven features and services.
- Perform feature engineering, data wrangling, and exploratory data analysis on large-scale structured and unstructured datasets.
- Build and maintain scalable AI infrastructure using cloud services (AWS, Azure, GCP) and MLOps best practices.
- Mentor junior AI engineers, guiding them in model development, evaluation, and deployment.
- Continuously improve model performance by leveraging new research, retraining on new data, and optimizing pipelines.
- Stay current with the latest developments in AI, machine learning, and deep learning through research, conferences, and publications.
Qualifications
Bachelor s or Master s degree in Computer Science, Data Science, Machine Learning or related field.14+ years of IT experience with a minimum of 6+ years of AIExperience in AI engineering, particularly with building LLM-based applications and prompt-driven architectures.Solid understanding of Retrieval-Augmented Generation (RAG) patterns and vector databases (especially Qdrant ).Hands-on experience in deploying and managing containerized services in AWS ECS and using CloudWatch for logs and diagnostics.Familiarity with AWS Bedrock and working with foundation models through its managed services.Experience working with AWS RDS (MySQL or MariaDB) for structured data storage and integration with AI workflows.Practical experience with LLM fine-tuning techniques, including full fine-tuning, instruction tuning, and parameter-efficient methods like LoRA or QLoRA.Strong understanding of recent AI advancements such as multi-agent systems, AI assistants, and orchestration frameworks.Proficiency in Python and experience working directly with LLM APIs (e.g., OpenAI, Anthropic, or similar).Comfortable working in a React frontend environment and integrating backend APIs.Experience with CI / CD pipelines and infrastructure as code (e.g., Terraform, AWS CDK).Skills Required
AWS ECS