
Global financial services firm
Applied AI ML Lead - Global Banking
Building and scaling secure agentic AI platforms and microservices, embedding AI into business UI workflows.
As an Applied AI ML lead in Global Banking Technology team , you will be a hands-on full-stack engineer and technical leader responsible for building and scaling agentic AI capabilities-including agents, MCP integrations, and orchestration services-and delivering AI-powered business UI use cases that embed these capabilities into real workflows. In parallel, you will partner closely with platform engineering teams to design and implement foundational platform services such as UI shell components, resolver servers, gateway services, and OPA-based policy enforcement.
You will own solutions end-to-end-from architecture and implementation through CI/CD, production readiness, and operational stability-while setting a high bar for engineering quality, security, resiliency, and developer experience.
Job Responsibilities
- Build and productionize agentic AI solutions agents, orchestrators, tool/function integrations, workflow/state management, and guardrails
- Implement MCP-style integrations to connect agents to enterprise tools/services with strong controls, auditability, and observability
- Deliver AI-enabled business UI experiences in partnership with product and UX, ensure usability, performance, and accessibility
- Design and develop Python and Java services (microservices and shared libraries) with strong API contracts and domain-driven design where applicable
- Partner with platform engineering to build/enhance core capabilities: Shell/component frameworks and reusable UI building blocks ;Resolver servers and orchestration backends ;Gateway services for routing, resiliency, and authN/authZ integration ;OPA-based policy enforcement and policy-as-code enablement
- Own end-to-end delivery, requirements, architecture, implementation, testing, CI/CD, deployment, monitoring, and production support
- Establish and uphold engineering standards for code quality, automated testing, performance tuning, observability (logs/metrics/traces), and resiliency
- Collaborate with security, risk, and controls partners to ensure solutions meet governance and compliance expectations for AI-enabled systems
- Produce reference architectures, templates, and paved paths to accelerate adoption across teams
Required Qualifications, Capabilities, and Skills
- 10+ years of hands-on software engineering experience delivering production-grade systems
- Strong proficiency in Python and Java, including clean architecture, design patterns, and performance-minded development
- Proven experience building distributed systems/microservices, including REST/gRPC API design and service decomposition
- Hands-on experience with orchestration/workflow patterns (state machines, job runners, event-driven services, or equivalent)
- Strong grounding in secure engineering practices authentication/authorization, secrets handling, least privilege, secure coding
- Experience with policy enforcement/authorization patterns, familiarity with OPA (or similar policy-as-code frameworks)
- Hands-on experience with Elasticsearch for building search, indexing, and analytics capabilities at scale
- Experience designing and implementing Spring Batch jobs for large-scale data processing and ETL workflows
- Solid SDLC discipline, code reviews, unit/integration testing, CI/CD, release hygiene, and production support ownership
- Strong communication and collaboration skills across product, UX, and multiple engineering teams
Preferred Qualifications, Capabilities, and Skills
- Experience building LLM/GenAI applications, including prompt/tool design, RAG patterns, evaluation approaches, and safety controls
- Familiarity with Model Context Protocol (MCP) concepts and building tool ecosystems for agent platforms
- Experience with React/TypeScript and enterprise UI shell/component frameworks
- Experience with Kafka/event streaming and asynchronous, event-driven architectures
- Cloud-native experience(AWS) with containers/Kubernetes and operational excellence (monitoring, alerting, incident response)
- Background delivering platforms in regulated environments with strong risk and control requirements
ABOUT US
JPMorgan Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
ABOUT THE TEAM
J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
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JPMorgan Chaseについて

JPMorgan Chase
PublicJPMorgan Chase & Co. is an American multinational banking institution headquartered in New York City and incorporated in Delaware. It is the largest bank in the United States, and the world's largest bank by market capitalization as of 2025.
300,000+
従業員数
New York City
本社所在地
$500B
企業価値
レビュー
10件のレビュー
3.8
10件のレビュー
ワークライフバランス
3.5
報酬
4.0
企業文化
3.8
キャリア
3.2
経営陣
2.8
68%
知人への推奨率
良い点
Good benefits and compensation
Supportive colleagues and environment
Flexible work arrangements
改善点
Long hours and heavy workload
Management issues and lack of direction
High stress and expectations
給与レンジ
44件のデータ
Mid/L4
Senior/L5
Mid/L4 · Applied AI ML Associate
2件のレポート
$188,500
年収総額
基本給
$145,000
ストック
-
ボーナス
-
$182,000
$195,000
面接レビュー
レビュー4件
難易度
3.0
/ 5
期間
14-28週間
内定率
50%
体験
ポジティブ 25%
普通 75%
ネガティブ 0%
面接プロセス
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
In-person/Final Interview
5
Offer
よくある質問
Behavioral/STAR
Past Experience
Culture Fit
Financial Knowledge
Case Study
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