Position:

Job Description:

Position Overview

As a AI 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 a strong foundation in machine learning and data science, with a strong focus on Generative 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.
• Develop Generative AI and LLM-powered applications using modern foundation models.
• Design and implement RAG pipelines, knowledge bases, semantic/hybrid search, and vector-based retrieval systems.
• Develop agentic AI and multi-step workflows using frameworks such as LangGraph 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 in Python and common ML/AI libraries.
• Hands-on experience developing and deploying ML/AI solutions in production.
• Practical experience with Generative AI and Large Language Models (LLMs).
• Experience with RAG, embeddings, vector databases, semantic search, or knowledge-based AI systems.
• Hands-on experience with LLM orchestration and agentic AI frameworks, preferably LangGraph 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-grade AI agents or multi-agent systems.
• Experience with LLM/RAG evaluation, observability, guardrails, and reliability techniques.
• Experience with cloud AI platforms such as AWS Bedrock, Azure OpenAI, or Google Vertex AI.
• Experience with Elasticsearch, OpenSearch, Solr, FAISS, pgvector, Pinecone, Milvus, or similar technologies.

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