Software Engineer II - Python - CIBT
As an Experienced Software Engineer at JPMorganChase within the Global Technology team, you serve as a member of an agile team to design and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You will contribute to building modern data- and AI-enabled applications, with an AI-first mindset—including the ability to leverage prompting techniques, LLM-driven workflows, and human-in-the-loop patterns to accelerate delivery and improve user outcomes while meeting strong security, control, and quality standards.
- Ciudad Autónoma de Buenos Aires, Argentina
- Full-time
- Posted Nov 5, 2026
Responsibilities
- Participates in the design and development of scalable and resilient systems using Python, SQL, React, AWS and other technologies to contribute to continual, iterative improvements for product teams
- Executes software solutions including design, development, and technical troubleshooting across the full stack where needed
- Partners with internal clients for requirements gathering, troubleshooting, and delivery of tools that enable better strategy, decisioning, and risk/cost management
- Creates secure, high-quality production code and maintains services and algorithms that run reliably with appropriate upstream/downstream systems
- Produces or contributes to architecture and design artifacts for applications while ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene, data quality, and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies, including modern AI engineering patterns
- Designs and implements LLM-enabled features (e.g., summarization, extraction, Q&A, reasoning assistants) with attention to reliability, latency, cost, and user experience
- Practices prompt-oriented development: iterating on prompts and system instructions as first-class artifacts, using versioning, test cases, and measurable evaluation criteria (quality, groundedness, safety)
- Implements patterns such as retrieval-augmented generation (RAG), tool/function calling, workflow orchestration, and human-in-the-loop review where appropriate
- Builds evaluation and monitoring approaches for AI features (automated checks, regression tests, guardrails, observability) and continuously improves quality based on production feedback
- Applies secure engineering practices to AI-enabled systems, including data minimization, access controls, safe handling of sensitive information, and resilience against prompt injection and misuse
Requirements
- Experience in a Financial Services
Nice to have: React, AWS, RAG, Semantic search, Embeddings, Prompt/version management, LLM evaluations, Model/service integration patterns, AI feature monitoring in production
Skills
Full description
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