Senior AI Engineer

About the role

A Senior AI Engineer is responsible for designing, developing, and delivering scalable Artificial Intelligence and Machine Learning solutions that address complex business requirements. The role focuses on Generative AI, Large Language Models (LLMs), Machine Learning, AI agents, RAG architectures, and cloud-native AI platforms, with a strong focus on Amazon Web Services (AWS). The Senior AI Engineer provides technical leadership across the AI engineering lifecycle, from solution architecture and experimentation through production deployment, optimization, monitoring, and continuous improvement. The role works closely with business stakeholders, software engineers, data teams, infrastructure teams, and technology partners to transform AI opportunities into secure, reliable, and measurable business solutions.

Key responsibilities

• Design, develop, deploy, and maintain scalable AI/ML and Generative AI solutions, with a strong focus on AWS cloud technologies.
• Lead the architecture and technical implementation of LLM, RAG, AI Agent, chatbot, and intelligent automation solutions for enterprise business use cases.
• Utilize AWS AI/ML services such as Amazon SageMaker, Amazon Bedrock, AWS Lambda, Amazon OpenSearch, Amazon S3, and related services to build production-ready AI platforms and applications.
• Develop, fine-tune, evaluate, and optimize machine learning and foundation models to improve accuracy, performance, scalability, and cost efficiency.
• Design and implement AI/ML APIs, microservices, data pipelines, and enterprise integrations to embed AI capabilities into business applications and workflows.
• Establish and implement MLOps/LLMOps practices, including model deployment, monitoring, evaluation, versioning, CI/CD, and continuous improvement.
• Lead technical Proof of Concepts (PoCs), experiments, benchmarks, and AI evaluations to assess new models, frameworks, and technologies.
• Ensure AI solutions meet security, privacy, data governance, responsible AI, and enterprise architecture standards.
• Provide technical leadership and mentoring to AI Engineers, Data Scientists, and development teams, including code, architecture, and technical design reviews.
• Research emerging AI technologies, foundation models, frameworks, and cloud services, and recommend solutions that provide business value, scalability, and cost efficiency.

About you

• Bachelor's or master's degree in computer engineering, Computer Science, Information Technology, or a related field
• 3+ years of experience in database design, data integration, data pipeline development, big data, or business intelligence applications in a competitive service industry
• Strong hands-on experience in AI/ML engineering and production deployment.
• Strong expertise in Generative AI, LLMs, RAG, AI agents, and foundation models.
• Strong experience with AWS cloud and AWS AI/ML services.
• Ability to design enterprise-scale AI architectures rather than focusing only on individual models or applications.
• Strong software engineering skills, including Python, API development, microservices, Git, testing, and CI/CD.
• Understanding of MLOps, LLMOps, model lifecycle management, and AI observability.
• Ability to evaluate AI technologies and make technology decisions based on business value, technical feasibility, security, scalability, and cost.
• Ability to lead technical projects and mentor other engineers.