Sr. Full Stack AI Engineer

Job Description

1. AI & LLM Engineering (25%)

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• Experience leveraging Large Language Models (LLMs) to solve business problems
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• Strong understanding of prompt engineering, prompt management, and GenAI solution design
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• Experience working with GenAI developer tools such as GitHub Copilot, Gemini, and Claude
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• Familiarity with AI strategy, implementation, and scaling AI-driven solutions
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2. Backend & Full Stack Engineering (25%)

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• Strong backend engineering background, as the role is heavily backend-focused
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• Hands-on experience with programming languages such as Java, Node.js, and Python
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• Familiarity with modern web application architectures
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• Expertise in API design, development, and integration
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3. Data Platform Engineering (25%)

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• Strong data engineering experience
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• Experience with data pipelines, data stores, orchestration frameworks, and distributed systems
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• Understanding of machine learning workflows and AI-enabled applications
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• Experience deploying and scaling AI/ML solutions in production environments
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4. Cloud Architecture, Scale & Security (25%)

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• Cloud-native development experience
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• Experience with Kubernetes and containerized application deployment
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• Experience with deployment patterns and scalable system design
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• Understanding of secure, enterprise-grade architecture
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The Skills You Bring

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These bullet points were taken out:

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• Deep expertise building AI-powered applications utilizing large language models (LLMs), agent frameworks, and orchestration platforms (e.g., OpenAI, Claude, Bedrock, LangChain, LangGraph).
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• Experience developing Retrieval-Augmented Generation (RAG) solutions, semantic search capabilities, and enterprise knowledge systems leveraging vector databases and retrieval frameworks.
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And the bolded below is the new/replacement

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• Bachelor's degree or equivalent experience with 8+ years of software engineering experience, or a Master's degree with 6+ years of experience.
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• Proven experience designing and delivering scalable, production-grade software solutions and distributed systems.
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• Strong experience using LLMs and Generative AI technologies to solve real business challenges.
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• Strong full-stack engineering background with modern languages and frameworks such as Python, TypeScript, Node.js, APIs, React, and Next.js.
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• Hands-on experience deploying and scaling applications within cloud environments such as AWS, Azure, or Google Cloud.
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• Experience with modern platform engineering and DevOps practices, including containers, Kubernetes, Infrastructure-as-Code, and cloud-native architectures.
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• Strong understanding of software architecture, design patterns, security, and reliability principles for enterprise-scale applications.
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• Excellent problem-solving skills, sound technical judgment, and a passion for building innovative solutions.
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• Ability to collaborate effectively across engineering, data, product, and business teams while driving initiatives from concept to production.
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