Senior Lead Software Engineer - Multiple Teams
About the job
- Formal training or certification on software engineering concepts and at least 5 years of applied experience.
- Demonstrated experience in system design, application development, testing, and operational stability for distributed systems and platform services.
- Strong hands-on depth in Python, including building and maintaining APIs and SDKs; ability to lead design and perform high-quality code and design reviews.
- Demonstrated experience with enterprise-authorized AI-assisted development tools, such as GitHub Copilot or Claude Code, and establishing practical team norms for validation and quality covering correctness, performance, and security in day-to-day engineering workflows.
- Experience delivering platforms involving Generative AI, including LLM orchestration patterns and agentic AI frameworks, with production-grade evaluation and monitoring practices.
- Practical experience with AWS, containerized platforms such as EKS or ECS, and Terraform or equivalent Infrastructure as Code.
- Required Databricks experience, including building and operating data and ML workloads on Databricks, such as pipelines, notebooks or jobs, Delta or feature datasets, and orchestration or integration with ML workflows.
- Comprehensive knowledge of the Software Development Life Cycle, agile delivery, CI/CD, and modern engineering quality controls.
- Strong communication skills with business-facing partners and technical stakeholders, and ability to translate strategy into execution and measurable outcomes.
- Contribute production code, primarily in Python, and own end-to-end delivery from design through production operations as a hands-on technical leader.
- Lead system and platform architecture for components supporting end-to-end ML workflows, including data transformation patterns, feature management integration, orchestration enablement, and model serving integration.
- Design and develop agentic AI capabilities that analyze workloads and generate optimization recommendations, including production-readiness evaluation approaches, monitoring, and feedback loops.
- Build and maintain reusable APIs, SDKs, and reference implementations that enable consistent platform adoption and reduce duplicated effort across teams.
- Partner with data scientists, ML engineers, and product teams to clarify requirements, define technical approaches, manage dependencies, and deliver measurable outcomes.
- Ensure platform reliability, scalability, performance, and cost efficiency through SLOs, proactive monitoring, incident response participation, root-cause analysis, and continuous improvement.
- Automate infrastructure provisioning, configuration, and CI/CD pipelines for platform services using Infrastructure as Code, promoting safe and repeatable deployments across environments.
- Drive adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes; establish consistent validation standards for correctness, performance, and security; and promote reuse of effective patterns.
- Produce architecture and design artifacts for platform components, ensuring alignment with enterprise standards and best practices.
- Mentor engineers through technical coaching, design reviews, and pairing, contributing to a strong culture of engineering excellence.
- Contribute to software engineering communities of practice and events that explore new and emerging technologies.
- Experience building ML platforms that integrate data engineering, feature management, and model serving into cohesive, developer-friendly workflows.
- Knowledge of AI/ML model integration, context engineering, and MCP-style patterns for tool or function integration.
- Exposure to Snowflake.
- Familiarity with observability and metrics tools such as CloudWatch, Dynatrace, or Datadog.
- AWS certifications.
About the company
JPMorgan Chase runs the largest bank in the United States, which serves households and small businesses as Chase and large companies, governments, and investors as J.P. Morgan. During the 2008 financial crisis it bought the failing investment bank Bear Stearns and lender Washington Mutual, and in 2023 it took over First Republic Bank after regulators seized it. Chase takes deposits and earns interest on credit cards, mortgages, and car loans, while the investment side earns fees for advising on mergers, raising money for companies, trading stocks and bonds, and managing wealth. Formed in a 2000 merger, JPMorgan Chase traces its roots to 1799 and is based in New York City.
Company Size
10,001+
Company Stage
IPO
Headquarters
New York City, New York
Founded
1799
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Simplify's Take
What believers are saying
- Growth is broad-based: every JPMorgan division posted record revenue in the June 2026 quarter, and trading jumped 35%.
- Stock grants gained value: shares rose 21% in three months, valuing JPMorgan at $965 billion in August 2026.
- Tech teams are well funded: JPMorgan's nearly $20 billion yearly tech budget is the largest in banking.
What critics are saying
- AI is shrinking some teams: Dimon said in July 2026 that AI cut up to 40% of certain roles.
- Plan on five office days a week: JPMorgan ended hybrid schedules for all staff in early 2025.
- It is fighting the president in court: Trump sued JPMorgan for $5 billion in January 2026 over his closed accounts.
What makes JP Morgan Chase unique
- It ranks first in investment banking: JPMorgan earned 9.3% of global deal fees in the first half of 2026.
- It trains future CEOs: 10 Fortune 500 chiefs were JPMorgan alumni in September 2025, fifth-most of any employer.
- Its payments arm is a hidden giant: JPMorgan says it processes $12 trillion a day across 160-plus countries.
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Benefits
Health Insurance
Flexible Work Hours
Paid Sick Leave
Paid Holidays
Growth & Insights and Company News
6 month growth
-9%1 year growth
-4%2 year growth
-4%Momei Qu, head of venture at PSP Growth, says Goldman Sachs and JPMorgan are becoming artificial intelligence (AI) stocks. She told Bloomberg's The Close that banks are tied to the AI buildout through debt financing, potential initial public offerings (IPOs) and mergers, though earnings do not show it yet. Lending was a bright spot last quarter. JPMorgan, Citigroup, and Wells Fargo posted a record $56.5 billion in combined net interest income, and JPMorgan's $107 billion outlook, excluding markets, beat the $103 billion consensus. Qu said investors are split on AI valuations: one camp excuses thin margins and heavy spending, while the other wants proof of returns. Anthropic holds its pre-IPO investor day on Wednesday. Bloomberg Intelligence analyst Herman Chan expects the Anthropic IPO to lift Goldman Sachs and Morgan Stanley. He warned that slower AI spending could cut banks' fee revenue from data center bond deals.
Four of Wall Street's biggest banks reported third quarter dealmaking fees of $8.47 billion, up 15% from a year earlier but down 7.5% from a banner second quarter. Goldman Sachs, JPMorgan Chase, Citigroup, and Wells Fargo said activity remains strong despite market volatility and higher borrowing costs. JPMorgan chief financial officer Jeremy Barnum said deals were "delayed rather than canceled" after a slowdown in late September, when volatility widened the gap between what buyers and sellers would accept. Goldman's fees rose 22% to $3.2 billion, led by record M&A advisory revenue. Wells Fargo's rose to $894 million, and Citigroup's rose 9% to $1.35 billion. Goldman chief executive officer David Solomon said some companies postponed initial public offerings (IPOs) in September rather than accept valuations 10% to 15% lower.
Goldman Sachs' equity trading revenue jumped 72% year over year to $6.44 billion in the third quarter, almost twice the $3.47 billion from fixed income. JPMorgan Chase's bond desk missed estimates by more than $500 million. JPMorgan's fixed income revenue fell 4% to $5.4 billion, its first decline in more than two years. Its equities desk rose 49% to $5.0 billion. Herman Chan, a senior US banks analyst at Bloomberg Intelligence, blamed expectations of prolonged high rates, which kept clients on the sidelines in September. "Goldman was the gold standard for the third quarter," he said. Higher rates still helped lenders. JPMorgan's net interest income rose 12.8% to $27.04 billion.
JP Morgan chief executive Jamie Dimon has warned savers against letting AI bots manage their money. He said customers could be liable for mistakes made by an agent acting on their behalf. "If people are using them, they should understand the risk," he said. JP Morgan will not let outside agents inside the company, calling it too risky for clients and the bank. The warning clashes with Silicon Valley's push. OpenAI has launched a "personal finance experience" for paid ChatGPT users in the US, and Anthropic is reportedly testing a similar tool. McKinsey found a quarter of UK consumers use AI for financial tasks at least monthly. It estimates savers could move up to £700bn out of low-interest accounts on chatbot advice.
Tenable, the exposure management company, has entered a credit agreement for a $400 million senior secured revolving credit facility. The facility is initially undrawn and gives the company more flexibility in how it allocates capital. Together with the convertible note financing announced in September, it completes the refinancing of Tenable's prior credit agreement, which included a Term Loan B facility. It also replaces the revolving credit facility that matured in July. The new loans mature on October 13, 2031, subject to a springing maturity date of 91 days inside the maturity of other material indebtedness. JPMorgan Chase Bank acted as administrative agent, and Cooley LLP advised Tenable.