Lead Python & SQL Application Developer - Vice President

Role

The Credit Risk Applications Technology Lead Analyst is a senior engineering leadership role responsible for designing, building, and evolving modern, scalable platforms that support credit risk analytics, workflows, and reporting. The role combines hands‑on development, system architecture, technical leadership, and AI‑enabled innovation with strong emphasis on microservices, cloud‑native design, and enterprise governance.

Key Responsibilities

• Architect, design, and deliver scalable Python‑based applications for credit risk analytics, workflows, and reporting.
• Design and evolve microservices architectures ensuring scalability, resiliency, observability, and maintainability.
• Build API‑driven services and enforce engineering standards for coding, testing, CI/CD, debugging, and production readiness.
• Partner with risk, product, and technology stakeholders to integrate platforms, identify enhancements, and enable new products and process improvements.
• Resolve high‑impact, complex initiatives through analysis of business processes and system flows.
• Apply AI and GenAI capabilities to modernize workflows, automate analysis, and augment credit risk insights.
• Serve as technical leader and mentor for mid‑level engineers and analysts, allocate work, and uphold enterprise controls and compliance.

How You’ll Work

• Operate with ownership, bias for action, and pragmatic innovation while delivering with enterprise discipline (stability, controls, transparency, audit readiness).
• Balance experimentation with responsibility and adapt as priorities change while maintaining long‑term system integrity.

Core Technical Skills / Requirements

• 10–15 years’ experience in application development or systems engineering in complex environments.
• Advanced proficiency in Python and SQL and strong software engineering fundamentals.
• Hands‑on experience building API‑driven services using FastAPI, Pydantic, and/or Django.
• Proven expertise in designing and implementing microservices architectures, inter‑service communication, resiliency patterns, and observability.
• Strong experience with Docker and Kubernetes for deploying and operating containerized production services.
• Experience in Linux environments, including shell scripting and operational troubleshooting.
• Strong track record implementing unit testing, TDD, and automated quality controls.
• Subject matter expertise in at least one application, platform, or service domain.

AI & Modern Engineering Tools

• Working knowledge of large language models (LLMs) and AI platforms (OpenAI, Anthropic, Google, Meta).
• Experience designing or contributing to LLM‑enabled solutions (copilots, workflow automation, analytics augmentation).
• Familiarity with prompt engineering, model integration patterns, and AI governance in enterprise settings.
• Exposure to AI‑assisted development practices (“vibe coding”) while maintaining engineering rigor.

Bonus / Differentiating Skills

• Experience with distributed data and compute platforms (Spark, PySpark, Hadoop, Hive).
• Hands‑on experience with graph databases, particularly Neo4j.
• Background in credit risk, financial risk management, or banking platforms.
• Experience modernizing or decomposing legacy monolithic systems in large enterprises.
• Proven delivery of GenAI/AI solutions in regulated or large‑scale environments.

Education

• Bachelor’s degree (or equivalent experience) in Computer Science, Engineering, Mathematics, or related STEM field. Master’s degree preferred.

Location & Time Type

• On‑Site/Resident in Chennai, Tamil Nadu, India. Full time.