Build and ship backend Python services and APIs incorporating LLM-based features and agentic workflows. Implement RAG, model integrations, caching, and concurrency controls. Use SQL, containers, Kubernetes, Terraform, and CI/CD; add observability and support production systems.
Role Overview
Required skills & experience
Preferred skills
About the TeamOur professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.
As a Software Engineer III at JPMorganChase within the AI/ML Technology, you will be a hands-on engineer responsible for building and shipping production software with a strong focus on AI-enabled capabilities. You will work across the full software development lifecycle—from requirements clarification and design through implementation, testing, deployment, and production support. You will develop backend services in Python, build APIs and microservices, implement LLM-based solutions including agentic workflows, and deliver into a multi-cloud environment using Terraform, Kubernetes, and CI/CD pipelines. This role offers you the opportunity to grow your expertise in applied AI engineering while contributing to systems that operate at enterprise scale.
Key responsibilities
- Deliver software through a disciplined software development lifecycle, working from well-defined requirements through design, implementation, testing, release, and production support
- Write maintainable Python code with unit and integration tests, debugging issues across application, API, data-access, and runtime layers
- Implement LLM-driven workflows including prompting, tool and function calling, routing, orchestration, and state handling to support multi-step agentic task execution
- Build and maintain inference-time integrations such as model gateways, APIs, caching, fallbacks, timeouts, and concurrency controls for production AI systems
- Implement retrieval-augmented generation components where applicable, including chunking, embeddings, retrieval, and grounding strategies
- Build REST and gRPC endpoints following agreed contracts, implementing authentication and authorization integration, input validation, error handling, and secure data handling practices
- Implement SQL-backed business logic powering APIs and microservices, including joins, aggregations, filtering, pagination, and transactional workflows
- Contribute to CI/CD pipelines and Git workflows, packaging and deploying services using containers and Kubernetes with support for safe rollouts and rollbacks
- Contribute to infrastructure-as-code using Terraform within established team patterns across modules, environments, and state management
Improve operability of services by adding and using observability tooling including logs, metrics, traces, dashboards, and alerts, and participate in incident response and root-cause analysis - Leverage enterprise-authorized AI coding assist 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
Required skills & experience
- Formal training or certification on software engineering concepts and proficient applied experience
- Strong hands-on Python development experience building backend services, including testing, packaging, dependency management, and maintainability
- Strong database and SQL proficiency, with experience implementing application logic and APIs on top of relational data
- Experience building APIs and microservices using REST or gRPC, including contracts, security basics, and observability
- Practical experience delivering LLM-based features as part of software systems, with familiarity with agentic patterns
- Working knowledge of delivery and operations including CI/CD, Git, containers, and Kubernetes
- Familiarity with Terraform and cloud infrastructure concepts in a multi-cloud environment
- Solid understanding of software engineering fundamentals and software development lifecycle practices including design, reviews, testing, release, and production support
- 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 and validate AI-generated outputs
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
Preferred skills
- Strong debugging and troubleshooting skills in distributed systems, including root-cause analysis and performance bottleneck identification using logs, metrics, and traces
- Experience improving code quality and reliability through test strategy improvements, refactoring, static analysis, and dependency hygiene
- Experience with deployment and operational best practices including safe releases, rollbacks, environment configuration, and incident readiness
- Familiarity with common architecture patterns such as event-driven designs, async processing, caching, API versioning, and backward compatibility
- Experience collaborating effectively in agile delivery, including estimating, breaking down work, documenting decisions, and communicating risks
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
Design, develop, and troubleshoot secure, production-grade software. Produce architecture and design artifacts, analyze large datasets, drive improvements in code quality and system architecture, and leverage enterprise AI-assisted tools while ensuring secure and responsible AI use.
Top Skills:
AIAWSDatabricksMachine LearningMobilePysparkPythonSQL
Financial Services
Design, develop, and maintain secure, high-quality production code and platform services for an AI/ML and data platform. Provide Databricks and AWS platform administration and engineering support, optimize infrastructure and CI/CD, apply SRE principles, automate remediation, and collaborate with data science, engineering, and vendors while guiding responsible AI-assisted development practices.
Top Skills:
SparkAutomation FrameworksAWSAws GlueCi/CdDatabricksDatabricks AdministrationDockerEnterprise Ai-Assisted Development ToolsJavaKubernetesMapreduceMonitoring ToolsPython
Information Technology • Legal Tech • Analytics
Design, build, and maintain components of the LNIP intelligence core platform, including a semantic search API and internal data curation tool. Implement secure coding standards, unit testing, code reviews, and use agentic development tools responsibly to accelerate development while ensuring quality.
Top Skills:
.NetAngularC#Claude CodeCloud DeploymentCoderCursorGithub CopilotJavaScriptOpenai CodexPysparkPythonReactSQLTypescriptVector Embeddings
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.
