Lead Software Engineer - AI, Python​/Java

Job Summary

Lead Software Engineer in the Firmwide AI/ML Deployment Platform team. Drive design, implementation, and deployment of AI solutions that unify observability data across AWS, Azure, and GCP to enable self‑service remediation, predictive outages, and reduced ticket volume.

• Build and deploy infrastructure solutions for seamless integration of control plane and user accounts.
• Design pipelines to ingest, aggregate, and correlate telemetry data (metrics, logs, traces) from multi‑cloud infrastructures.
• Architect and implement closed‑loop automation playbooks that allow infrastructure to auto‑remediate common, repeatable failure modes without human intervention.
• Drive team adoption of enterprise‑authorized AI‑assisted engineering practices to improve code quality, delivery speed, and operational outcomes, establishing consistent validation standards.
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including AI‑assisted development and automation capabilities, to improve the value realized by automation.
• Build and operationalize LLM/machine learning models for anomaly detection, predictive health monitoring, and forecasting system degradations.
• Integrate the AI engine with ticket data and map observability insights against ticket trends, cluster repetitive issues, and quantify the platform’s impact on reducing Mean Time to Resolution (MTTR).
• Create user‑friendly self‑service portals or conversational AI interfaces that allow non‑expert teams to diagnose and fix infrastructure issues safely.

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Strong proficiency in Python and Java, with experience integrating LLM/ML models, time‑series forecasting pipelines, and NLP for log/ticket clustering.
• Advanced experience with configuration management tools and automated workflow engines.
• Hands‑on experience building custom webhooks, APIs, and integrations with ticketing systems such as Service Now or Jira Service Management.
• Competency in managing large‑scale, streaming data infrastructure using cloud‑native data warehouses (e.g., Snowflake).
• Expertise in multi‑cloud architectures across AWS, Azure, and GCP, including on‑prem.
• Experience with enterprise observability stacks such as Open Telemetry, Prometheus, and Dynatrace.
• Demonstrated experience leading effective use of approved AI‑assisted software development tools and setting team expectations for validating AI outputs.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations and secure handling of inputs/outputs.

• Practical experience applying generative AI and agentic workflows to accelerate development, with strong judgment, governance, and quality control over AI‑produced outputs.
• Experience optimizing performance and reliability of AI‑powered user interfaces and proficiency in the React framework.
• Knowledge of multi‑cloud domains and LLM integration.
• Experience in API development and design.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans, and does 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.