Lead Machine Learning Engineering

Job description

**Role Overview** We are looking for a Senior AI Engineer who can design, build, and deploy production-ready AI solutions using modern Large Language Models (LLMs), AI agents, and cloud-native architectures. The ideal candidate combines strong software engineering fundamentals with hands-on experience building scalable AI applications, integrating foundation models, and delivering business value through Generative AI. **Key Responsibilities** - Design, develop, and maintain AI-powered applications using Large Language Models (LLMs) and Generative AI technologies - Build AI agents and Retrieval-Augmented Generation (RAG) solutions to enable intelligent workflows and knowledge-based applications. - Integrate leading AI platforms such as Azure OpenAI, Amazon Bedrock, Google Vertex AI, or similar services. - Develop scalable backend services and APIs using Python and modern frameworks such as FastAPI. - Collaborate with frontend engineers to deliver end-to-end AI applications using technologies such as React. - Design prompt engineering strategies to improve model accuracy, reliability, and user experience. - Implement intelligent routing, semantic search, vector databases, and knowledge retrieval solutions. - Deploy and manage cloud-native AI applications using AWS and Infrastructure as Code tools such as Terraform. - Build and maintain CI/CD pipelines, containerized applications, and cloud infrastructure using Docker and DevOps best practices. - Evaluate emerging AI frameworks, tools, and models to continuously improve platform capabilities. - Collaborate with Product Managers, Architects, and Engineering teams to translate business requirements into scalable AI solutions. - Mentor engineers and contribute to technical leadership, architecture discussions, and engineering best practices. **Required Qualifications** - 10+ years of experience in Software Engineering with recent hands-on experience building Generative AI solutions. - Strong experience with Python and REST API development. - Experience developing production AI applications using Large Language Models (LLMs). - Hands-on experience with AI agent frameworks such as LangChain, CrewAI, or similar technologies. - Experience implementing Retrieval-Augmented Generation (RAG) architectures. - Experience integrating AI platforms such as Azure OpenAI, Amazon Bedrock, Google Vertex AI, or equivalent services. - Strong understanding of prompt engineering techniques and AI application design patterns. - Experience developing scalable cloud applications on AWS. - Experience with Docker, Terraform, CI/CD pipelines, and Infrastructure as Code. - Experience with SQL and NoSQL databases. - Familiarity with React or modern frontend technologies. - Experience working within Agile software development environments. - Strong understanding of software architecture, API design, and distributed systems. - Experience working in cross-functional and multicultural teams. **Working Style** - Strong communication skills: able to clearly explain complex AI concepts to both technical and non-technical audiences. - Proactive mindset: identifies opportunities for innovation and continuously explores new AI technologies. - Ownership and accountability: takes responsibility for delivering reliable, scalable, and maintainable AI solutions. - Collaborative attitude: works effectively across product, engineering, architecture, and business teams. - Adaptability: thrives in a rapidly evolving AI landscape and embraces continuous learning. - Attention to detail: prioritizes quality, security, observability, and responsible AI practices. - Customer-oriented thinking: focuses on solving real business problems through practical AI solutions. - Continuous learner: stays current with advancements in LLMs, AI frameworks, cloud services, and software engineering best practices