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Salary
≈ $23k – $58k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 5+ years exp

Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Oct 21, 2026. Campbell Global scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Campbell Global brings more than three decades of experience and leadership to sustainable timberland and natural resource investment management.

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 Commercial & Investment bank, 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 breakdown technical problems
  • Develops secure and 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

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Hands-on practical experience delivering system design, application development, testing, and operational stability for production systems.
  • Advanced in one or more programming languages, with strong fundamentals in JavaScript and TypeScript.
  • Strong hands-on React + Next.js engineering experience. Strong UX/UI engineering capability
  • Strong hands-on Java backend engineering, caching and data layer experience. Hands-on AWS experience
  • 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
  • Proficient in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • In-depth knowledge of the financial services industry and their IT systems

Preferred qualifications, capabilities, and skills

  • Experience with LLMs and agent frameworks, including prompt/tool orchestration patterns and evaluation strategies (quality, safety, regression testing, monitoring).
  • Production experience with containers/Kubernetes, feature flags, and modern observability stacks.
  • Performance tuning and resilience patterns such as caching strategies, async workflows, circuit breakers, timeouts/retries, and backpressure.
  • Experience with progressive delivery and experimentation practices (feature flags, phased rollouts, A/B testing), and operating services against defined reliability targets (SLIs/SLOs).
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