We're looking for a Senior GenAI Machine Learning Engineer to join a global technology organization driving the next generation of AI-powered products and intelligent automation. This is an exciting opportunity to work at the forefront of Generative AI, designing and deploying production-grade LLM applications, AI agents, and scalable machine learning solutions that will transform customer experiences and business operations.
Working alongside AI leaders, data scientists, software engineers, and product teams, you'll play a key role in developing enterprise-grade GenAI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI frameworks, and cloud-native technologies. This is a highly hands-on engineering role where you'll help shape the organization's global AI strategy while building innovative AI applications from concept to production .
Responsibilities
- Design, develop, and deploy Generative AI applications powered by Large Language Models (LLMs).
- Build and scale AI agents and agentic workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies.
- Develop intelligent customer-facing and internal AI solutions, including conversational AI and AI-powered automation.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines, prompt engineering strategies, and LLM evaluation frameworks.
- Build and deploy custom AI solutions using AWS Bedrock and leading foundation models.
- Fine-tune, evaluate, and optimize LLMs using proprietary and external datasets.
- Develop scalable APIs and backend services to support real-time AI inference and production workloads.
- Implement guardrails, monitoring, testing, and governance to ensure AI solutions are secure, reliable, accurate, and responsible.
- Collaborate with Data Science, Engineering, and Product teams to deliver scalable AI-powered products.
- Contribute to the organization's global Generative AI roadmap by evaluating emerging technologies, frameworks, and best practices.
- Document technical solutions and provide technical expertise across cross-functional teams.
Requirements
- 6+ years of experience in Artificial Intelligence and Machine Learning.
- 3+ years of hands-on experience in Machine Learning Engineering, Natural Language Processing (NLP), Generative AI, or Large Language Model (LLM) technologies.
- Strong experience building applications using LLM orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or similar.
- Solid understanding of transformer architectures, prompt engineering, Retrieval-Augmented Generation (RAG), guardrails, and LLM evaluation methodologies.
- Strong Python programming skills with experience using machine learning frameworks such as PyTorch and scikit-learn.
- Experience designing, developing, and deploying production-grade machine learning and Generative AI solutions.
- Experience working with cloud platforms, preferably AWS, including AWS Bedrock.
- Experience building scalable APIs and backend services for AI applications.
- Strong understanding of software engineering best practices, system integration, and production deployment.
- Excellent analytical and problem-solving skills.
- Strong communication skills with the ability to explain complex AI concepts to both technical and non-technical stakeholders.
- Ability to work independently while collaborating effectively within cross-functional Agile teams.
- Experience with Voice Conversational AI or Contact Centre AI solutions.
- Knowledge of distributed training pipelines for Large Language Models.
- Experience implementing LLMOps or MLOps practices in production environments.
- Familiarity with responsible AI, AI governance, model monitoring, and compliance frameworks.
- Experience working with multi-modal AI models and agentic AI architectures.
- Experience developing enterprise-scale AI products in cloud-native environments.
Please contact Ella Godinez at [Confidential Information] for a confidential discussion.
EA License no: 16S8066
