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.
AI Fluency - AI-first mindset
4+ years of experience
- We expect the candidate to go beyond personal AI use and apply AI to improve system design and scale how teams work in practice.
- Approaches system design, architecture, or technical decisions by 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 the team's work and introduces AI-powered improvements, including code reviews, AI-assisted testing, intelligent alerting, or document generation.
- Applies advanced prompting techniques to tackle ambiguous, multi-step, or domain-specific problems.
- Thinks through how AI-assisted solutions will be tested, deployed, monitored, and maintained.
Technical Environment
- Core stack: Python, SQL, numerical and optimization libraries, quantitative research and backtesting tools, machine-learning and LLM frameworks, and agent orchestration platforms.
- Operating environment: Cloud or hybrid data and model platforms, containerized and distributed services, approved model endpoints, secure data integrations, and enterprise governance controls.
- Workflow: Version-controlled research and software, reproducible experiments, architecture and peer review, CI/CD, automated testing, model validation, and staged readiness gates.
- Quality & reliability: Deterministic risk services, point-in-time data controls, observability, audit trails, reconciliation, model evaluation, human-in-the-loop controls, incident management, and governance reporting.
What will help you be successful in this role
- Master's or Doctoral degree preferred, or equivalent experience, in a quantitative discipline, Computer Science, Engineering, Machine Learning, or a related field.
- 8 or more years of experience across quantitative engineering, data science, machine learning, or software engineering, including at least three years leading complex AI or quantitative systems.
- Expert-level Python skills and strong command of numerical methods, optimization, statistics, time-series analysis, portfolio construction, and risk analytics.
- Experience building production LLM or agent-based systems, including tool orchestration, retrieval, evaluation, groundedness controls, observability, and reliability engineering.
- Strong architecture and distributed systems experience, with a track record of moving research concepts into secure, scalable, and supportable platforms.
- Deep judgement in model risk, data quality, reproducibility, governance, and human oversight, plus the communication and influence skills to explain technical trade-offs and limitations to senior stakeholders.
Nice to have skills
- Experience in asset management, quantitative equity, market-neutral or long/short strategies, factor models, portfolio optimization, or investment-risk technology.
- Experience modeling transaction costs, liquidity, borrow, turnover, tracking error, exposure limits, and scenario or stress risk.
- Experience with model serving, Kubernetes, vector databases, workflow engines, distributed computing, or enterprise AI platforms.
- Experience establishing AI governance, model validation, independent challenge, human-in-the-loop controls, or audit-ready technical standards.
Work Schedule & Location
This position will work a hybrid schedule, 3 days/week in our San Ramon or San Mateo offices.
Franklin Templeton offers employees a competitive and valuable range of total rewards - monetary and non-monetary - designed to support their well-being and recognize their time, talents, and results. Along with base compensation, employees are eligible for an annual discretionary bonus, a 401(k) plan with a generous match, and recognition rewards. We also offer a comprehensive benefits package, which includes a range of competitive healthcare options, insurance, and disability benefits, employee stock investment program, learning resources, career development programs, reimbursement for certain education expenses, paid time off (vacation / holidays / sick / leave / parental & caregiving leave / bereavement / volunteering / floating holidays) and a motivational wellbeing program. We expect the annual salary for this position to range between $189,200 - $233,800, depending on location and level of relevant experience, plus discretionary bonus.
#MID_SENIOR_LEVEL
At Franklin Templeton, we believe your benefits should support your life, your goals, and your future. That's why we offer a comprehensive Total Rewards package designed to help you thrive both personally and professionally.
Highlights of our benefits include:
- Paid Time Off: Three weeks of PTO in your first year
- Health Coverage: Competitive medical, dental, and vision insurance to support your well-being
- Retirement Savings: 401(k) plan with an 85% company match on pre-tax and/or Roth contributions, up to IRS limits
- Equity & Investing: Employee Stock Investment Plan (ESIP) with discounted share purchase opportunities
- Learning Education Assistance Program (LEAP): To support your ongoing growth and career advancement
- Employee Investment Benefits: Opportunity to purchase company funds with no sales charge
Franklin Templeton is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all applicants and 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.
Artificial intelligence or automated tools may be used to assist in the screening, assessment, or selection of applicants for this position.