Sr. Full Stack AI Engineer

1. AI & LLM Engineering (25%)

• 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

2. Backend & Full Stack Engineering (25%)

• 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

3. Data Platform Engineering (25%)

• 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

4. Cloud Architecture, Scale & Security (25%)

• 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

The Skills You Bring

These bullet points were taken out:

• 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.

And the bolded below is the new/replacement

• 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.