Senior AI Engineer / Senior Machine Learning Engineer

Position:

Job Description:

Position Overview

As aAI Engineer / Senior Machine Learning Engineer – GenAI & Agentic AI at Arrow Electronics, you will play a key role in developing and deploying intelligent AI solutions that address complex business and engineering challenges.

The role is built on astrong foundation in machine learning and data science, with a strong focus onGenerative AI, Large Language Models (LLMs), RAG, knowledge bases, and agentic AI systems.

You will work across the full AI lifecycle, from data exploration and model development to production deployment, evaluation, optimization, and continuous improvement. You will collaborate with software engineers, data engineers, product teams, and domain experts across a multinational environment.

Key Responsibilities

• Design, develop, evaluate, and deploy machine learning and AI solutions for real-world problems.
• Apply strong ML and data science fundamentals and model evaluation.
• DevelopGenerative AI and LLM-powered applications using modern foundation models.
• Design and implementRAG pipelines, knowledge bases, semantic/hybrid search, and vector-based retrieval systems.
• Developagentic AI and multi-step workflows using frameworks such asLangGraph and LangChain.
• Build agents capable of tool usage, reasoning, routing, state management, and multi-step task execution.
• Develop evaluation and monitoring approaches for ML, LLM, RAG, and agentic AI systems.
• Collaborate with technical and business stakeholders to translate complex problems into practical AI solutions.

Qualifications

Required

• 3–6 years of professional experience in data science, machine learning, AI engineering, or a related field.
• Strong machine learning and data science fundamentals are mandatory.
• Strong proficiency inPython and common ML/AI libraries.
• Hands-on experience developing and deployingML/AI solutions in production.
• Practical experience withGenerative AI and Large Language Models (LLMs).
• Experience withRAG, embeddings, vector databases, semantic search, or knowledge-based AI systems.
• Hands-on experience withLLM orchestration and agentic AI frameworks, preferablyLangGraph and/or LangChain.
• Understanding of agentic architectures, tool calling, workflow orchestration, state management, and multi-step AI workflows.
• Strong analytical, problem-solving, and communication skills.

Preferred / Plus

• Experience building production-gradeAI agents or multi-agent systems.
• Experience with LLM/RAG evaluation, observability, guardrails, and reliability techniques.
• Experience with cloud AI platforms such asAWS Bedrock, Azure OpenAI, or Google Vertex AI.
• Experience with Elasticsearch, OpenSearch, Solr, FAISS, pgvector, Pinecone, Milvus, or similar technologies.

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