Python Terraform AWS DevOps MLOps Lead Software Engineer at JPMC Candidate Experience page

Columbus, Ohio, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Sep, 26

Salary

0.0

Posted On

21 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Terraform, AWS, Kubernetes, MLOps, DevOps, CI/CD, Docker, Helm, GitOps, Prometheus, Grafana, AI-assisted Engineering, MLflow, SageMaker, Postgres

Industry

Financial Services

Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within the Consumer & Community Banking Digital Cloud team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. Job responsibilities * Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems * Develops secure high-quality production code, and reviews and debugs code written by others * Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team. * 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. * Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems * Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture * Design and develop a scalable ML platform to support model training, deployment, and monitoring * Build and maintain infrastructure for automated ML pipelines, ensuring reliability and reproducibility supporting different model frameworks and architectures * Set up monitoring and reliability for both infrastructure and models utilizing Prometheus and Grafana * Code infrastructure with Terraform and utilizing Python for automation * Perform DevOps in Kubernetes (K8s), Docker, Helm, GitOps, and CI/CD pipelines (Jenkins, GitLab CI) Required qualifications, capabilities, and skills * Formal training or certification on software engineering concepts and 5+ years applied experience * 8+ years of hands‑on software/platform engineering experience, including leading cloud‑native delivery for business‑critical systems. * Expert Infrastructure as Code with Terraform (modules, state backends, workspaces, CI integration, policy controls). * Expert proficiency in Python for platform automation, tooling, and systems scripting; familiarity with Bash/YAML/Helm. * Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security. * Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices * Deep experience with CI/CD (e.g., Jenkins, Spinnaker/Argo), artifact management, and automated testing strategies * Strong AWS/public cloud knowledge (VPC, ALB/NLB, ECR/EKS, IAM, KMS, CloudWatch/CloudTrail) and cloud networking fundamentals * Experience with MLOps tools and platforms (e.g., MLflow, Amazon SageMaker, Google VertexAI, Databricks, BentoML, KServe, Kubeflow) * Practical experience applying agentic AI/LLM capabilities to DevSecOps use cases (e.g., assisted troubleshooting, code/IaC generation with review, runbook automation) with attention to accuracy, guardrails, and auditability * Containerization & DevOps: Expert skills in Kubernetes (K8s), Docker, Helm, GitOps, and CI/CD pipelines (Jenkins, GitLab CI). Preferred qualifications, capabilities, and skills * Experience deploying models using Canary, Blue/Green, or Shadow deployment strategies * Previous experience deploying & managing ML models is beneficial * Experience working in a highly regulated environment or industry * Strong knowledge of AWS, Azure, or GCP, including serverless architectures, storage solutions, and network configuration. * Postgres experience * Monitoring & Reliability: Experience setting up monitoring for both infrastructure and models (drift detection, model accuracy) using Prometheus/Grafana. * Understanding of data versioning and ML models lifecycle management Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 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 [https://careers.jpmorgan.com/us/en/how-we-hire/faqs] for more information about requesting an accommodation. Equal Opportunity Employer/Disability/Veterans Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

Responsibilities

Lead the design and development of a scalable ML platform and automated pipelines to support model training and deployment. Drive the adoption of AI-assisted engineering practices and manage cloud-native infrastructure using Terraform and Kubernetes.