Build and maintain Python services, scripts, and data/AI pipelines.
Write efficient SQL for analysis, data validation, debugging, and performance tuning.
Rapidly triage incidents: reproduce issues, isolate root cause, and implement fixes.
Develop and iterate on AI applications (e.g., LLM-powered workflows, retrieval, evaluation).
Design and implement agentic systems (tool-using agents, orchestration, guardrails, memory patterns where appropriate).

Key requirements

Build and maintain Python services, scripts, and data/AI pipelines.
Write efficient SQL for analysis, data validation, debugging, and performance tuning.
Rapidly triage incidents: reproduce issues, isolate root cause, and implement fixes.
Develop and iterate on AI applications (e.g., LLM-powered workflows, retrieval, evaluation).
Design and implement agentic systems (tool-using agents, orchestration, guardrails, memory patterns where appropriate).

Jobs at JPMorganChase

27 active roles from this employer in the JobMatcher catalog.

All company jobs

Jobs at JPMorganChase

27 active roles from this employer in the JobMatcher catalog.

All company jobs

About the role

Lead Software Engineer – Python, Observability

Lead Software Engineer role focusing on Python, observability, and AI-enabled data platforms within JPMorganChase's Risk Corporate Technology. You will be an integral member of an agile team that builds, enhances, and delivers trusted market-leading technology products in a secure, stable, and scalable environment. As a core technical contributor, you will drive software solutions across multiple domains to support the firm’s objectives.

Responsibilities

Qualifications:

Build and maintain Python services, scripts, and data/AI pipelines.
Write efficient SQL for analysis, data validation, debugging, and performance tuning.
Rapidly triage incidents: reproduce issues, isolate root cause, and implement fixes.
Develop and iterate on AI applications (e.g., LLM-powered workflows, retrieval, evaluation).
Design and implement agentic systems (tool-using agents, orchestration, guardrails, memory patterns where appropriate).
Create monitoring and observability: logging, metrics, traces, and alerting for AI and data services.
Drive enterprise-approved AI-assisted engineering practices to improve code quality and delivery speed, while establishing validation standards and promoting reuse of effective patterns.
Apply SDLC toolchain knowledge to improve automation and the value realized by automation.
Document system behavior, known failure modes, and support procedures.
Formal training or certification in software engineering concepts and 5+ years of applied experience; minimum 8 years industry experience.
Strong Pyt

About the role

Lead Software Engineer – Python, Observability

Lead Software Engineer role focusing on Python, observability, and AI-enabled data platforms within JPMorganChase's Risk Corporate Technology. You will be an integral member of an agile team that builds, enhances, and delivers trusted market-leading technology products in a secure, stable, and scalable environment. As a core technical contributor, you will drive software solutions across multiple domains to support the firm’s objectives.

Responsibilities

Qualifications:

Build and maintain Python services, scripts, and data/AI pipelines.
Write efficient SQL for analysis, data validation, debugging, and performance tuning.
Rapidly triage incidents: reproduce issues, isolate root cause, and implement fixes.
Develop and iterate on AI applications (e.g., LLM-powered workflows, retrieval, evaluation).
Design and implement agentic systems (tool-using agents, orchestration, guardrails, memory patterns where appropriate).
Create monitoring and observability: logging, metrics, traces, and alerting for AI and data services.
Drive enterprise-approved AI-assisted engineering practices to improve code quality and delivery speed, while establishing validation standards and promoting reuse of effective patterns.
Apply SDLC toolchain knowledge to improve automation and the value realized by automation.
Document system behavior, known failure modes, and support procedures.
Formal training or certification in software engineering concepts and 5+ years of applied experience; minimum 8 years industry experience.
Strong Pyt

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