Lead Machine Learning Engineering

Role overview A senior AI engineer is needed to design, build, and deploy production-ready AI solutions using modern large language models, AI agents, and cloud-native architectures. The role combines strong software engineering fundamentals with hands-on experience integrating foundation models and delivering measurable business value through Generative AI applications.

Responsibilities - Design, develop, and maintain AI-powered applications using large language models and Generative AI technologies. - Build AI agents and Retrieval-Augmented Generation solutions that enable intelligent workflows and knowledge-based applications. - Integrate leading AI platforms such as Azure OpenAI, Amazon Bedrock, or Google Vertex AI. - Develop scalable backend services and APIs in Python using frameworks such as FastAPI. - Collaborate with frontend engineers to deliver end-to-end AI experiences using technologies such as React. - Design prompt engineering strategies, semantic search, vector databases, and intelligent routing patterns. - Deploy and operate cloud-native AI applications on AWS using Infrastructure as Code tools such as Terraform, Docker, and CI/CD pipelines. - Evaluate emerging AI frameworks and models, mentor engineers, and contribute to architecture and engineering best practices.

Requirements - 10+ years in software engineering with recent hands-on experience building Generative AI solutions. - Strong Python and REST API development skills. - Production experience with LLMs, AI agent frameworks such as LangChain or CrewAI, and RAG architectures. - Hands-on integration with Azure OpenAI, Amazon Bedrock, Google Vertex AI, or equivalent services. - Experience with AWS, Docker, Terraform, CI/CD pipelines, and Infrastructure as Code. - Working knowledge of SQL and NoSQL databases, React or modern frontend technologies, and Agile software development. - Strong grasp of software architecture, API design, distributed systems, and cross-functional multicultural teamwork.

Nice to have - Experience mentoring engineers and contributing to technical leadership and architecture discussions.

Benefits and work setup - Cloud-native, Agile delivery environment focused on scalable, production-grade AI platforms.