Senior AI Engineer
EPAM · зарплата не указана · Kuala Lumpur, Malaysia · сайт компании · опубликовано 5 июня 2026 г.
Описание вакансии
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
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