Job Description
1. AI & LLM Engineering (25%)
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- Experience leveraging Large Language Models (LLMs) to solve business problems
- Strong understanding of prompt engineering, prompt management, and GenAI solution design
- Experience working with GenAI developer tools such as GitHub Copilot, Gemini, and Claude
- 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
- Hands-on experience with programming languages such as Java, Node.js, and Python
- Familiarity with modern web application architectures
- Expertise in API design, development, and integration
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3. Data Platform Engineering (25%)
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- Strong data engineering experience
- Experience with data pipelines, data stores, orchestration frameworks, and distributed systems
- Understanding of machine learning workflows and AI-enabled applications
- 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
- Experience with Kubernetes and containerized application deployment
- Experience with deployment patterns and scalable system design
- 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).
- 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.
- Proven experience designing and delivering scalable, production-grade software solutions and distributed systems.
- Strong experience using LLMs and Generative AI technologies to solve real business challenges.
- Strong full-stack engineering background with modern languages and frameworks such as Python, TypeScript, Node.js, APIs, React, and Next.js.
- Hands-on experience deploying and scaling applications within cloud environments such as AWS, Azure, or Google Cloud.
- Experience with modern platform engineering and DevOps practices, including containers, Kubernetes, Infrastructure-as-Code, and cloud-native architectures.
- Strong understanding of software architecture, design patterns, security, and reliability principles for enterprise-scale applications.
- Excellent problem-solving skills, sound technical judgment, and a passion for building innovative solutions.
- Ability to collaborate effectively across engineering, data, product, and business teams while driving initiatives from concept to production.
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