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Metro location, AI/backend skillset demand, and desirable modern stack increase applicant competition.
Backend and AI integration skills are broadly transferable across industries with limited domain lock-in.
Multiple mandatory technical skills (Python, Kubernetes, Terraform, AWS, CI/CD, security) create moderately strict filters.
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Design, build, and operate backend services and REST APIs powering Galaxy's AI products, integrating with AI Suite APIs like AWS Bedrock and SageMaker.
Implement AI-powered application features using LLMs, embeddings, RAG, and prompt engineering; ensure quality and reliability of AI features in production.
Contribute across the stack as needed, including data models, CI/CD pipelines, infrastructure, production issue resolution, and collaboration with cross-functional teams.
Strong experience with Python backend development, REST API design, CI/CD pipelines, automated testing, and distributed systems fundamentals.
Familiarity with AI integration, including working with Generative AI concepts like LLMs, RAG, embeddings, prompt engineering, and AWS Bedrock or equivalent.
Experience with cloud platforms, especially AWS, and infrastructure tools such as Kubernetes, Terraform, Docker; Jenkins experience is a plus.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced backend engineer comfortable shipping AI-powered features by consuming AI platform APIs rather than building AI models or platforms from scratch.
Demonstrates operational ownership with experience in production reliability, monitoring, performance tuning, and security (AuthN/AuthZ, secrets management).
Prior experience or strong interest in financial services, digital assets, AI infrastructure, or related regulated environments is highly desirable but not explicit requirement.