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Senior GenAI Machine Learning Engineer

Job description

Role Overview

We are seeking a Senior GenAI Machine Learning Engineer to drive the development of Generative AI initiatives globally. The successful candidate will leverage Large Language Models (LLMs), agentic workflows, orchestration frameworks, and cloud technologies to build next-generation AI-powered products and services.

Working closely with the Head of AI, Data Scientists, Engineers, and Product Managers, this role will contribute to the design, development, deployment, and scaling of AI solutions across the organization.

Key Responsibilities

  • Build and integrate Generative AI applications for customer interactions using LLMs and orchestration frameworks.
  • Design, develop, and scale internal AI agents and customer-facing agentic solutions.
  • Deploy custom AI solutions using AWS Bedrock and foundation models.
  • Fine-tune and evaluate large language models using proprietary and external datasets.
  • Develop scalable APIs and backend services for real-time AI inference.
  • Implement monitoring, testing, and guardrails to ensure reliability, privacy, and response quality.
  • Support AI governance initiatives and Responsible AI practices.
  • Collaborate with Data Science teams on AI use cases including document processing, claims decisioning, and reporting.
  • Contribute to the global GenAI roadmap and technology strategy.
  • Document solutions and collaborate with cross-functional stakeholders.
  • Stay current with emerging trends, tools, and technologies in AI and machine learning.


Requirements

  • 6+ years of experience in AI and Machine Learning.
  • 3+ years of experience in Machine Learning Engineering, NLP, Generative AI, and LLM technologies.
  • Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
  • Strong understanding of transformer architectures, prompt engineering, RAG, guardrails, and LLM evaluation methodologies.
  • Advanced English proficiency (minimum B2/C1).
  • Hands-on experience with Python and machine learning frameworks such as PyTorch and Scikit-learn.
  • Experience with AWS cloud technologies, preferably AWS Bedrock.
  • Knowledge of MLOps and LLMOps practices.
  • Experience with Conversational AI or Voice AI is a plus.
  • Strong analytical, problem-solving, communication, and stakeholder management skills.
  • Ability to work independently and collaboratively in an international environment.


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