Senior AI Engineer

Job Purpose:The Senior AI Engineer is responsible for designing, developing, deploying, and optimizing advanced Artificial Intelligence solutions that support business transformation and innovation initiatives. The role provides technical leadership in the implementation of Machine Learning models, Large Language Models (LLMs), Agentic AI solutions, AI Operations (AIOps), and enterprise-scale AI platforms while ensuring scalability, reliability, security, and measurable business value.Key Accountabilities:Design, develop, and deploy AI and Machine Learning solutions to address business and operational challenges.Build and optimize Generative AI applications leveraging Large Language Models (LLMs) and enterprise AI frameworks.Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and knowledge retrieval technologies.Develop Agentic AI solutions utilizing multi-agent frameworks and orchestration platforms.Build, maintain, and optimize APIs and backend services supporting AI-driven applications.Implement and manage AI model deployment, serving, monitoring, and lifecycle management processes.Establish MLOps and AIOps best practices to ensure reliable model delivery and operational excellence.Design and maintain scalable data pipelines, feature engineering workflows, and AI-ready data architectures.Optimize AI inference performance, model serving infrastructure, and resource utilization.Collaborate with business stakeholders, data engineers, architects, and technology teams to identify and implement AI use cases.Implement monitoring, observability, and evaluation frameworks to track AI model quality, performance, and reliability.Support cloud-native AI deployments and infrastructure across public cloud platforms.Provide technical guidance, mentorship, and knowledge sharing to engineering teams.Contribute to AI strategy, architecture standards, governance practices, and innovation initiatives.Minimum Qualifications:Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a related field.Professional certifications Artificial Intelligence, Machine Learning, Data Science, Data Engineering, Cloud Platforms.Minimum Experience:+5 years of experience in Artificial Intelligence, Machine Learning, Data Engineering, or Software Engineering.Proven experience designing and deploying AI and Machine Learning solutions in enterprise environments.Hands-on experience with Large Language Models (LLMs), Generative AI, and RAG-based architectures.Experience implementing MLOps practices and production-grade AI systems.Experience working with cloud platforms and containerized application environments.Proven experience delivering AI initiatives from design through production deployment and operational support.Job-Specific Skills:Python Programming and Advanced SQL.API Development and Integration.Large Language Models (OpenAI, Azure OpenAI, Hugging Face).Retrieval-Augmented Generation (RAG).Vector Databases (Qdrant, Pinecone, Chroma).LangChain, LangGraph, and Multi-Agent Systems.Machine Learning and Advanced Analytics.Kubernetes, Docker, and Container Orchestration.CI/CD Pipelines and MLOps Practices.vLLM, Model Serving, and AI Inference Optimization.Data Engineering Tools including Airflow, Kafka, and ETL Pipelines.Cloud Platforms (AWS, Microsoft Azure, or Google Cloud Platform).AI Monitoring and Evaluation Tools (LangFuse, MLflow, Prometheus, Grafana).AI Platform Engineering and AIOps.Enterprise Data Management and Data Architecture.Strong analytical, problem-solving, and troubleshooting skills.Excellent communication, stakeholder management, and technical leadership capabilities.