Leads software engineering for private cloud infrastructure across on-premise and public cloud environments. Designs, develops, troubleshoots, and maintains secure production systems; creates architecture artifacts; applies AI-assisted development tools; and advances DevOps, SRE, automation, reliability, and scalability. Collaborates with globally distributed teams, guides engineers’ career development, promotes responsible AI usage, and contributes to engineering communities and continuous improvement initiatives.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Senior Lead Software Engineer at JPMorganChase within the Atlas On Premise and Next Generation Infrastructure team, you will be a seasoned member of a small, high-paced agile team spanning the UK, Ireland, and the US. You will play a pivotal role in delivering a first-class private cloud offering, focusing on enabling multiple hypervisor platforms and striving for a consistent end user experience across both on premise and public cloud environments. You will not only be a software engineer, but also an innovator — leveraging AI tooling and continuous improvement practices to drive quality and efficiency. Your deep knowledge of software engineering, experience with DevOps and Site Reliability Engineering principles, and passion for new technologies will help shape the future of our infrastructure solutions. As a leader, you will be expected to guide and support other members of the team in their career progression.
Job responsibilities
- Execute software solutions across design, development, and technical troubleshooting, thinking beyond routine approaches to build innovative solutions and break down complex technical problems
- Create secure, high-quality production code and maintain algorithms and systems that support robust private cloud infrastructure
- Produce architecture and design artifacts for complex applications, ensuring design constraints are met throughout the software development lifecycle
- Leverage enterprise-authorized AI-assisted coding tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards
- Apply 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
- Drive adoption of DevOps and Site Reliability Engineering principles across the team to improve system reliability, scalability, and operational efficiency
- Collaborate with cross-functional teams across the UK, Ireland, and the US to deliver consistent end user experiences across on premise and public cloud environments
- Contribute to software engineering communities of practice and events that explore new and emerging technologies
- Champion a team culture of diversity, inclusion, opportunity, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and advanced applied experience
- Proficient in coding in Java, GoLang, or equivalent modern programming languages
- Experience developing, debugging, and maintaining code in a large, complex corporate environment
- Solid understanding of agile methodologies, including continuous integration/continuous delivery, application resiliency, and security
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Experience with DevOps and Site Reliability Engineering principles
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
Preferred qualifications, capabilities, and skills
- Familiarity with hypervisor platforms such as VMware, OpenShift, or Hyper-V, as well as bare metal environments
- Experience with public cloud technologies (e.g., AWS, Azure, or Google Cloud)
- Demonstrated passion for innovation, AI, and continuous improvement practices
- Ability to thrive in a small, high-paced, globally distributed team environment
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.
Similar Jobs
Financial Services
Lead an agile team to design, build, test, and operate scalable public cloud foundational services (Atlas). Provide technical guidance, influence product and architecture decisions, mentor engineers, prototype solutions, and drive adoption of firmwide frameworks and best practices for cloud infrastructure.
Top Skills:
AWSSentinelTerraform
Financial Services
Lead design and delivery of secure, scalable data and LLM-based AI systems for Global KYC and risk assessment. Develop production code, define architecture and engineering standards, mentor engineers, govern agentic AI and LLM applications, and drive cross-team adoption of cloud-native, data-intensive solutions.
Top Skills:
Apache IcebergApi DesignAWSAzureBig Data ProcessingData LakeDatabricksGCPLlmLlm Orchestration FrameworksMicroservicesModel Serving InfrastructureNosql DatabasesObservability ToolsPysparkPythonRelational DatabasesSnowflakeSparkVector Stores
Financial Services
Lead and mentor engineering teams to design, build, and operate secure, scalable AI/ML data platform components. Develop and review production-grade code, drive architecture and tooling decisions, embed enterprise AI-assisted development practices, ensure resiliency/security, and promote reuse and engineering best practices across teams.
Top Skills:
Ai-Assisted Development ToolsArtificial IntelligenceAsynchronous MessagingAWSCachingCloud NativeContainer OrchestrationInfrastructure-As-CodeJavaMachine LearningMicroservicesNoSQLReactRelational DatabasesRestful ApisServerless ComputingSpring BootTypescript
What you need to know about the Edinburgh Tech Scene
From traditional pubs and centuries-old universities to sleek shopping malls and glass-paneled office buildings, Edinburgh's architecture reflects its unique blend of history and modernity. But the fusion of past and future isn't just visible in its buildings; it's also shaping the city's economy. Named the United Kingdom's leading technology ecosystem outside of London, Edinburgh plays host to major global companies like Apple and Adobe, as well as a growing number of innovative startups in fields like cybersecurity, finance and healthcare.
