Machine Learning Engineer III - AI Agent Engineer - Digital and Technology Partners - Onsite/Hybrid

Responsibilities

• Assume full ownership of the design, development, deployment, governance, and continuous evolution of AI agent ecosystems and autonomous workflows.
• Leverage Large Language Models (LLMs), multi-agent systems, Retrieval-Augmented Generation (RAG), orchestration frameworks, and enterprise integrations to deliver end-to-end agentic AI solutions.
• Collaborate with cross-functional teams, including data scientists and product managers, to ensure the successful deployment and robust maintenance of machine learning models.
• Oversee the continuous monitoring and timely updating of deployed models to guarantee enduring performance and reliability.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, or a related field.
• 4+ years of relevant experience in machine learning and back-end software development.
• 1+ years of hands-on experience building and deploying Generative AI, LLM, RAG, Copilot, or Agentic AI solutions in production environments.
• Experience with LLM platforms and frameworks such as Azure AI Foundry, Azure OpenAI, OpenAI, Anthropic, LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar technologies.
• Experience building RAG architectures utilizing vector databases such as Pinecone, Azure AI Search, Elasticsearch, Weaviate, Chroma, or equivalent platforms.
• Demonstrated end-to-end machine learning system development and operation experience, covering the complete Software Development Life Cycle (SDLC).
• Proficiency in multiple programming languages and machine learning frameworks and tools.
• Solid experience with both SQL and NoSQL databases.
• Extensive experience with Big Data technologies like Apache Spark.
• Hands-on experience in Unix environments.
• Praactical knowledge and experience with at least one cloud system among AWS, Azure, or Google Cloud.
• Familiarity with continuous development and integration systems such as Jenkins, Git, Azure DevOps, and Terraform.
• Proven history in developing, deploying, and operating efficient and reliable machine learning systems.
• Strong leadership and effective communication skills to facilitate cross-functional collaboration throughout the organization.