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High — Tier-1 brand, popular backend title, mid-level (2+ years), and broad skill requirements attract many qualified applicants.
Medium — core engineering skills are transferable, but enterprise banking and responsible AI constraints increase domain specificity.
High — explicit 2+ years, mandatory backend/data/AI tech stack, and regulated enterprise environment increase filter strictness.
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Develop, design, and troubleshoot backend components of software products with focus on secure, stable, and scalable solutions.
Write and maintain high-quality code primarily in Python and related technologies (Airflow, Spark, databases, AI/ML tools).
Utilize enterprise-authorized AI-assisted software development tools to improve code quality, delivery speed, and productivity, while validating AI outputs.
2+ years of applied software engineering experience with formal training or certification.
Proficiency in system design, application development, testing, and operational stability within large corporate environments.
Strong hands-on skills in Python, data backbones (Airflow, Spark), core database concepts (relational and document), cloud technologies, and AI/ML technologies (GenAI/LLMs, agentic AI).
Experience using AI-assisted software development tools and understanding of responsible AI use, including security and resiliency considerations.
Practical experience across the full Software Development Life Cycle with exposure to agile methodologies like CI/CD and application resiliency/security.
Strong backend engineering focus with advanced knowledge of AI/ML technologies and algorithms.
Ability to critically evaluate AI-generated outputs within development workflows and apply security best practices for data and code.