Lead Software Engineer - Python Gen AI

JPMorganChase; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

JPMorgan Chase in Bengaluru seeks a Senior Manager of Software Engineering to lead multiple teams and drive day-to-day implementation aligned with compliance, risk controls, and strategic best practices.

You will own automation, security, data accountability, and scalable AI-assisted development across AO workstreams, delivering reliable, scalable software at enterprise scale.

Qualifications

• Bachelor’s degree in software engineering or equivalent with 8+ years of experience.
• Expertise in at least one tech stack with a track record of delivering production software.
• Strong experience with Kubernetes, AWS/cloud platforms, and Big Data/ETL pipelines.
• Strong development experience in Java, Python, or Scala.
• Experience leading enterprise AI-assisted development adoption across engineering teams.
• Understanding of responsible AI use, governance, and data handling in engineering workflows.
• Knowledge of core infrastructure components and problem solving across domains.
• Deep proficiency in SRE practices: reliability, scalability, security, and toil reduction.
• Observability expertise using Grafana, Dynatrace, Prometheus, Datadog, Splunk.
• CI/CD proficiency with Jenkins, GitLab, Terraform.

Responsibilities

• Design, code, test, and deliver automation (including LLMs/agents) to reduce manual work and streamline remediation workstreams.
• Govern application risk, controls, and compliance; ensure adherence to firm standards and drive remediation of findings.
• Own security and data accountability for the application, including proper authentication, vulnerability hygiene, and data retention.
• Coordinate across product and engineering at scale to prioritize and drive AO workstreams with urgency.
• Lead adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation with human validation and secure handling of data.
• Apply SDLC toolchain knowledge to improve automation value and capacity initiatives.
• Run resilient production services end-to-end with monitoring, secure configs, and incident/change management.
• Champion site reliability culture and influence across teams to improve service levels.
• Lead data-driven initiatives to improve reliability and reduce toil across platforms.
• Collaborate to define SLIs/SLOs and align stakeholders; share knowledge via internal forums.

Skills

Kubernetes

AWS/other cloud platforms

Big Data/ETL pipelines

Java, Python, or Scala

AI-assisted development

Responsible AI governance

Observability

CI/CD tools

SRE best practices

Education

Bachelor’s degree (or equivalent experience) in software engineering

Tools

Grafana

Dynatrace

Prometheus

Datadog

Splunk

Jenkins

GitLab

Terraform

Job description

Job Description:

As Manager of Software Engineering at JPMorgan Chase within the Corporate Technology, you lead multiple teams and manage day-to-day implementation activities by identifying and escalating issues and ensuring your team’s work adheres to compliance standards, business requirements, and tactical best practices.

Job responsibilities

• Design, code, test, and deliver automation(including LLMs/agents) to eliminate manual operational work and streamline AO workstreams’ remediations (e.g., control items, security vulnerabilities, upgrades, and FARM findings).
• Govern application risk, controls, and compliance:own adherence to firm standards, partner with Technology Risk & Controls, manage Technology Lifecyle Management (TLM), and drive closure of issues/findings (e.g., FARM) through effective remediation and evidence management.
• Own security and data accountability for the application:ensure strong authentication/authorization, vulnerability and certificate hygiene, and proper data registration/classification plus compliant storage/retention/disposal.
• Coordinate across product and engineering at scaleto prioritize and drive execution with a clear sense of urgency for AO workstreams (including influencing/coaching teams and aligning execution across large developer communities).
• Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns across teams.
• 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 and support capacity unlock initiatives.
• Run resilient, well-operated production services end-to- end:implement monitoring/logging and anomaly detection, maintain secure network configurations/least privilege, and lead/support incident/problem/change management and recovery/resiliency readiness.
• Demonstrates and champions site reliability culture and practices and exerts technical influence throughout your team
• Leads initiatives to improve the reliability and stability of your team’s applications and platforms using data-driven analytics to improve service levels
• Collaborates with team members to identify comprehensive service level indicators and stakeholders to establish reasonable service level objectives and error budgets with customers
• Documents and shares knowledge within your organization via internal forums and communities of practice

Required qualifications, capabilities, and skills

• Bachelor’s degree (or equivalent experience) in a software engineering discipline with8+ yearsof experience.
• Expertise in at least one technology stack with a track record of designing, coding, testing, and delivering production software.
• Strong experience withKubernetes,AWS/other cloud platforms, andBig Data/ETL pipelines(e.g., Hortonworks/AWS), including scalable data processing solutions.
• Strong development experience inJava, Python, or Scala, with excellent debugging and troubleshooting skills for complex production issues.
• Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining ways of working (review/validation expectations), measuring outcomes, and ensuring secure handling of data.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and governance expectations; ability to coach engineers on compliant and effective usage.
• Working knowledge of core infrastructure components (routers, load balancers, cloud products, containers, compute, storage, networks) and ability to solve complex, mission-critical problems across domains.
• Deep proficiency inSRE best practices: reliability, scalability, performance, security, enterprise system architecture, and toil reduction; able to implement within an application or platform.
• Deep knowledge of software applications and technical processes, with emerging depth in one or more technical disciplines.
• Proficiency inobservability(white/black box monitoring, SLO alerting, telemetry collection) using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, etc.
• Proficiency inCI/CDtools (e.g., Jenkins, GitLab, Terraform), plus ability to troubleshoot networking issues, solve data structure/algorithm problems, teach new languages, and collaborate across stakeholder levels.

Preferred qualifications, capabilities, and skills

• Certified in Python , Gen AI.