Senior AI/ML Engineer

Senior AI/ML Engineer

Senior AI/ML Engineer
Job Details:
Compensation: $160,000 - $200,000
Work Environment: Hybrid (2 days onsite)
Office Location: Glenview, IL
Benefits: Health, Dental, Vision, 401K, PTO, Strong employer contribution to retirement

Key Responsibilities

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• Design, develop, deploy, and support AI-powered applications, copilots, agents, and workflow automations.
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• Build production-ready AI solutions using LLMs, RAG, vector databases, embeddings, semantic search, and prompt engineering.
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• Develop AI agents that securely leverage enterprise data, knowledge repositories, APIs, and business workflows.
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• Integrate AI solutions with cloud platforms, enterprise systems, and collaboration tools across Azure and AWS.
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• Create reusable AI components, prompts, connectors, and frameworks to accelerate future AI development.
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• Partner with business and technical stakeholders to translate use cases into scalable AI products with measurable business impact.
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• Ensure AI solutions meet enterprise standards for security, governance, privacy, and responsible AI.
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Required Qualifications

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• 7+ years of software engineering experience, including 2+ years building enterprise AI solutions.
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• Hands-on experience with:
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  • LLM application development
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  • RAG architectures
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  • Prompt engineering
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  • Embeddings and vector search
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  • LLM APIs and model evaluation
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  • Agentic AI and workflow orchestration
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• Strong Python development skills and hands-on experience with AI/ML technologies.
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• Experience building LLM-based applications using RAG, prompt engineering, embeddings, vector search, and agentic AI frameworks.
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• Proven success delivering production-ready AI solutions that drive automation, productivity, or business efficiency.
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• Experience deploying and supporting applications in Azure and/or AWS environments.
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Preferred Qualifications

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• Experience with Azure AI Foundry, Azure AI Search, Copilot Studio, Amazon Bedrock, SageMaker, Pinecone, OpenSearch, or similar AI platforms.
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• Knowledge of NLP, semantic search, vector databases, and model evaluation.
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• Experience integrating AI solutions through APIs, containers, Azure Functions, or AWS Lambda.
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• Familiarity with AI governance, security, and responsible AI best practices.
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