This role exists to own the design and delivery of significant services and components within the AI Platform, and to raise the engineering standard of the teams around it.
The Senior Software Engineer will lead technical design for features and integrations, build production services, set testing and observability expectations, and mentor less experienced engineers.
Success means the platform gains capabilities that are secure, observable, and supportable, with design decisions documented and technical risk surfaced early rather than discovered in production.
How you will add value
Core Responsibilities
You will own the technical design and delivery of backend services, APIs, data integrations, and reusable libraries within an assigned domain.
You will translate ambiguous requirements into architecture options, estimates, sequencing, and clear acceptance criteria.
You will set and uphold standards for automated testing, code quality, secure coding, performance, and operational readiness.
You will build observability, structured logging, alerting, and failure handling into services so that issues are detectable before users report them.
You will lead code and design reviews, mentor engineers, and raise the overall technical capability of the team.
You will diagnose complex production incidents, drive root-cause analysis, and deliver systemic fixes rather than point remedies.
You will partner with product, architecture, data, and Legal, Risk and Compliance to ensure solutions meet enterprise security and control requirements.
You will maintain high- and low-level technical documentation and evaluate new tools and approaches against measurable delivery value.
Strategic Responsibilities
You will approach system design, architecture, or technical decisions by considering where AI can meaningfully improve the solution, not just the development process.
You will evaluate trade-offs between AI-assisted and traditional approaches with practical judgement.
You will identify repetitive, manual, or error-prone processes in the team's work and introduces AI-powered improvements, including code reviews, AI-assisted testing, intelligent alerting, or document generation.
You will apply advanced prompting techniques to tackle ambiguous, multi-step, or domain-specific problems.
You will think through how AI-assisted solutions will be tested, deployed, monitored, and maintained.
Technical Environment
Core stack: Python, SQL, modern backend services and APIs, with supporting data-processing and testing libraries.
Operating environment: Cloud or hybrid environments, containerized services, secure enterprise data integrations, and approved model endpoints.
Workflow: Git-based development, CI/CD, automated testing, agile delivery, and infrastructure or configuration as code.
Quality & reliability: Observability, structured logging, performance testing, security controls, code-quality gates, and incident management.
What will help you be successful in this role
Experience, Education & Certifications
Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
5+ years of professional software engineering experience, including production backend, distributed, or data-intensive systems.
Demonstrated experience with automated testing, CI/CD, containerization, observability, secure coding, and operational support.
Track record of leading technical design for non-trivial features and mentoring other engineers.
Experience in asset management, wealth management, portfolio analytics, trading, or risk technology would be a plus.
Hands-on experience with LLM applications, AI agents, retrieval-augmented generation, or model evaluation would be a plus.
Experience with cloud platforms, Kubernetes, workflow orchestration, event-driven systems, or time-series data would be a plus.
Experience moving data-science prototypes into secure, supportable production services would be a plus.
Technical Skills
Advanced Python skills and strong experience with APIs or microservices, SQL, data processing, software design, and system integration.
Soft Skills
Strong written and verbal communication skills, sound technical judgement, and the ability to collaborate across engineering, product, and control functions
Advanced English proficiency
Franklin Templeton is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all applicants and existing employees, and we evaluate qualified applicants without regard to ancestry, age, color, disability, genetic information, gender, gender identity, or gender expression, marital status, medical condition, military or veteran status, national origin, race, religion, sex, sexual orientation, and any other basis protected by federal, state, or local law, ordinance, or regulation.
Franklin Templeton is committed to maintaining an ethical, transparent, and accountable work environment, which contributes to the integrity and success of the organization. We encourage the reporting of any known or suspected violations of national as well as EU laws through appropriate reporting channels available internally and externally. We ensure that whistleblowers who report such breaches are protected from retaliation and provided with safe and confidential reporting mechanisms.
Please see the procedure below – both in Polish and English
Artificial intelligence or automated tools may be used to assist in the screening, assessment, or selection of applicants for this position.
