Join EPAM Malaysia as a Senior AI Engineer and lead the charge in creating cutting-edge AI solutions that solve complex, real-world problems. You'll design and deploy scalable ML pipelines using ML frameworks and data platforms while harnessing the power of cloud platforms. Collaborate with cross-functional teams to transform business challenges into innovative data-driven solutions, leveraging your expertise in Python, SQL and MLOps frameworks. Responsibilities Design and implement end-to-end AI systems including inference pipelines, agent workflows and tool-calling architectures Build and manage context orchestration for LLMs, covering system prompts, memory, retrieval and structured inputs Engineer latency-aware and cost-efficient fallback strategies across models and providers Develop backend services for prompt routing, response handling and tool execution using Python or Node.js Implement observability for AI systems including logging, metrics, tracing and quality monitoring Maintain CI/CD pipelines for safe, repeatable deployments of AI services Integrate and deploy AI-powered software solutions into scalable enterprise environments, translating business requirements into robust system designs Collaborate with cross-functional teams, ensure compliance with data protection and AI governance and document architectures and implementation decisions Requirements Solid software engineering experience with hands-on work with AI/ML or LLM systems, and a Bachelor's or Master's degree in Computer Science, Data Science or a related field Proficient in Python, with experience in SQL or NoSQL databases, REST APIs and backend integration Demonstrated expertise in LLM-based solution development, prompt engineering, NLP, semantic models and agent-style architectures Skilled in fine-tuning and evaluating LLMs, building automated AI pipelines for training, testing, deployment and monitoring Experience with the Spark or Apache ecosystem, scalable data and AI architectures and cloud computing platforms Proficient in containerization technologies such as Docker and Kubernetes with experience in GPU orchestration and cost optimization Familiarity with CI/CD pipelines, DevOps tooling and enterprise-scale architectures Strong analytical thinker and communicator, results-driven, customer-focused and actively following new AI advancements and industry best practices No visa sponsorship available Nice to have Experience integrating with LLM APIs from providers like OpenAI, Claude, or comparable platforms Direct involvement in building or maintaining Retrieval-Augmented Generation (RAG) systems, including work with vector databases and embedding pipelines Familiarity with model safety measures, implementation of AI guardrails or responsible AI best practices
