Software Engineer

At Franklin Templeton, we believe success is built through powerful partnerships. As a forward thinking asset manager, we build dynamic relationships with clients, understand their goals, and navigate complex markets together. We leverage cutting edge strategies and deep insights to unlock opportunities for long term wealth creation. Our talented, global teams bring expertise that is both broad and unique.

From our welcoming, inclusive, and supportive culture to our globally diverse business, we offer opportunities not only to help you reach your potential, but also to contribute to our clients’ success.

About The Department

Our direct team is based in the USA. The team supports batch systems for FADB, our funds accounting database, and for GPW, the downstream system that reports product performance. The immediate team is currently three full-time employees.

We are seeking an experienced and adaptable Software Engineer to design and deliver resilient, secure, well-observed software for Franklin Templeton's Technology & Operations organization, and to raise engineering standards on the team. This is a senior-level individual contributor role with a stronger emphasis on design and system quality.

You will own the design and delivery of services and applications from idea to production and beyond, make sound architecture decisions, build for security and reliability, and help teammates through code review and shared tooling.

Your work gives the business secure, reliable and well-observed platforms.

Core Responsibilities

How you will add value

• - You will design and build scalable back-end services, batch processes and APIs in Python (Django and FastAPI) and Oracle PL/SQL, developing new code and configuration for complete features.
• - You will define service health metrics, and use logging, metrics and tracing to find and fix production problems safely, including failures in batch processes.
• - You will build security into design: authentication, authorization, API protection and secrets management.

Strategic Responsibilities

• - You will make and document architecture decisions on distributed systems, scalability, high availability and event-driven design, and propose high-level solutions.
• - You will design GitLab CI/CD pipelines and containerized deployments on AWS (Lambda, ECS Fargate, EC2) that release database, API and application changes together safely, and establish test strategy and automation.
• - You will design and build AI-enabled features where they add value, and evaluate their quality and safety.

Team & Collaboration

• - You will review source code and effort estimates of more junior engineers, and build shared libraries and developer tooling.
• - You will plan and coordinate cutover and implementation activities, build effective working relationships with other technical teams, and resolve ownership questions between teams with evidence.

Experience, Education & Certifications

What will help you be successful in this role

1-4 Years Of Experience

• - Uses AI assistants as a natural part of their development workflow: for writing code, debugging, writing tests, generating documentation, and exploring unfamiliar domains.
• - Decomposes a task into parts, translates those parts into effective prompts, and iterates on those prompts until the task is complete.
• - Treats AI-generated outputs as drafts, not final, and refines them before incorporating.
• - Actively explores new AI tools, techniques, and capabilities.

4+ years of experience

• - Approaches system design, architecture, or technical decisions, considering where AI can meaningfully improve the solution, not just the development process.
• - Evaluates trade-offs between AI-assisted and traditional approaches with practical judgement.
• - Identifies repetitive, manual, or error-prone processes in their team's work and introduces AI-powered improvements, including but not limited to code reviews, AI-assisted testing, intelligent alerting, or document generation.
• - Applies advanced prompting techniques to tackle ambiguous, multi-step or domain specific problems.

Technical Environment

• - Core stack: Python and Oracle PL/SQL, with a Django web application (using Django REST) and FastAPI REST APIs, both running on ECS Fargate.
• - Operating environment: AWS cloud, with some workloads on Linux EC2 and some container-based (ECS Fargate).
• - Workflow: Git and GitLab CI/CD, AWS Lambda workflows and S3.
• - Quality and reliability: service health metrics, logging, tracing, production debugging, automated testing.

Technical And Soft Skills

• - Strong programming skills in Python, including Django