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Job Description The Machine Learning Center of Excellence (MLCOE) team partners across the firm to create and share Machine Learning Solutions for our most challenging business problems. In this role you will work and collaborate with a team comprised of a multi-disciplinary community of experts focused exclusively on Machine Learning. On this team you will work with cutting-edge techniques in disciplines such as Deep Learning and Reinforcement Learning. As a Lead Software Engineer at JPMorgan Chase within the Corporate Sector – AIML Data Platforms and Machine Learning Center of Excellence Team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. Job Responsibilities Design, develop, and maintain production-grade Python services and APIs. Architect and implement high-throughput, low-latency distributed systems in AWS environments. Build and manage scalable cloud-native applications leveraging Amazon EKS, ECS, MSK (Kafka), SQS, and S3. Develop reusable service frameworks, shared libraries, and modular application components. Design and implement infrastructure-as-code solutions using Terraform and CloudFormation. Create and maintain monitoring, alerting, and observability solutions utilizing Datadog, Dynatrace, and Splunk. Deploy and support applications in production environments while ensuring adherence to service-level objectives (SLOs) and service-level agreements (SLAs). Implement secure-by-design engineering practices, automated testing, and deployment strategies including blue/green and canary releases. Review code, provide architectural guidance, and mentor engineers on software engineering best practices. Collaborate with product managers, platform engineering teams, and site reliability engineers to deliver scalable business solutions. Drive adoption of enterprise-approved AI-assisted engineering practices to improve code quality, operational excellence, troubleshooting, and delivery efficiency. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. Required Qualifications, Capabilities, And Skills Formal training or certification in software engineering concepts and 5+ years of applied experience. Advanced proficiency in Python programming, object-oriented design, and modular software architecture. Experience building and operating large-scale, high-performance cloud-native services within AWS environments. Hands-on experience with AWS technologies including EKS, ECS, MSK (Kafka), SQS, and S3. Strong experience implementing Infrastructure as Code (IaC) solutions using Terraform and/or CloudFormation. Expertise in designing, deploying, and supporting distributed systems in production environments. Experience with observability, monitoring, logging, and alerting platforms such as Datadog, Dynatrace, and Splunk. Strong understanding of API design, microservices architecture, and scalable system design patterns. Experience implementing automated testing, CI/CD pipelines, deployment automation, and secure software engineering practices. Demonstrated experience utilizing approved AI-assisted software development tools for coding, code review, testing acceleration, troubleshooting, and operational support. Strong understanding of responsible AI usage, application security, resiliency requirements, compliance standards, and mentoring engineers on engineering best practices. Preferred Qualifications, Capabilities, And Skills Strong knowledge of distributed systems reliability patterns, including resiliency engineering, self-healing architectures, backpressure management, and idempotency. Experience optimizing real-time and event-driven architectures at scale, particularly with Kafka-based messaging systems. Experience implementing end-to-end observability, automated operational runbooks, and proactive monitoring frameworks. Familiarity with CI/CD best practices, canary deployments, blue/green deployment strategies, and release automation within cloud environments. Familiarity with Generative AI and Large Language Model (LLM) technologies and experience building engineering solutions that leverage AI/LLM platforms. ABOUT US JPMorganChase, 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 offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 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. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans About The Team Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.