AI Modernization Senior Lead Software Engineer
On-siteJersey City, New Jersey, United States
Job Summary
Build agentic systems that ingest decades of mainframe logic and produce verified, production-ready modern services by translating legacy COBOL, JCL, and DB2 into structured specifications. Design multi-agent orchestration layers, tool-use patterns, and guardrails to ensure output correctness for financial calculations while extending ETL and CDC pipelines for end-to-end migrated workflows. Own LLMOps for the toolchain, managing deployment, monitoring, cost, and latency optimization for 24/7 production reliability. Partner with domain SMEs across Credit, Money Market, and Tax to validate agent outputs and iterate rapidly on prompt strategies and model selection. Drive adoption of AI-assisted engineering practices to improve code quality and delivery speed while establishing measurable validation standards for secure coding and automated testing.
Required Qualifications
- Formal training or certification on software engineering concepts
- 5+ years applied experience
- Hands-on experience building LLM-based applications — agentic architectures, RAG pipelines, prompt engineering, and evaluation frameworks
- Strong software engineering fundamentals: distributed systems, event-driven architectures, API design, testing practices, and cloud platforms (AWS/EKS/ECS)
- Expert proficiency with AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) as core daily workflow
- Strong experience with Python development in production environments
- Demonstrated ability to operate and debug complex systems — you own what you ship
- Clear communicator who can articulate technical trade-offs to both engineers and business stakeholders
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls
- Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
Desired Qualifications
- Experience with legacy systems, mainframe technologies (COBOL, JCL, DB2), or large-scale migration programs
- Familiarity with workflow orchestration (Temporal, Airflow) and event sourcing / CDC patterns and experience building code analysis, translation, or verification tooling
- Experience with Kafka, PostgreSQL, and container orchestration (Kubernetes/EKS)
- Background in financial services — wealth management, brokerage, or capital markets processing
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