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About The Role
Design and build quantitative technology solutions powering a systematic, data-driven investment platform for a $46bn global investment management function. Focused primarily on fixed income and credit markets while also supporting alternative investment strategies across the platform. Partner closely with portfolio managers, traders, quantitative researchers, risk managers, and investment operations teams to design and implement scalable tools for portfolio construction, trading, analytics, and investment decision-making. Role demands a highly hands-on senior engineer who can develop robust data pipelines, analytics frameworks, and front-office workflows, consistently with best-practices across analytics teams at Arch. Contribute to the ongoing development of AIM's internal investment platform, including backend services and APIs supporting AIMI Native — the firm's internal web-based investment management interface. Reporting directly to the Head of Quant Engineering, with close collaboration across engineering and technology partners at AIM.
It is preferred, but not required, that candidates are willing and open to relocation to Bermuda. If not, this role is can sit remotely in the US, but candidates must be EST time zone based.
Job Responsibilities
- Design and build front-office quantitative tools and infrastructure supporting portfolio managers, traders, and alternative asset managers across fixed income and credit strategies
- Develop and maintain data ingestion and processing pipelines integrating data from major financial vendors (ICE, Bloomberg, FactSet, Kamakura, LSEG, and others)
- Build and enhance portfolio analytics, optimization frameworks, and simulation environments for portfolio construction, risk analysis, and strategy implementation
- Design and implement daily trading order generation and portfolio management workflows, integrating quantitative tools with front-office systems to streamline the investment process
- Partner with portfolio managers and traders to translate investment workflows and business requirements into scalable technical solutions
- Develop backend services and API interfaces for the AIMI internal investment platform, enabling seamless interaction between analytics systems and front-office applications
- Build scalable, maintainable Python-based analytics libraries and services following software engineering and quantitative development best practices
- Ensure data quality, integrity, and consistency across all datasets used for portfolio construction, risk analysis, and trading decisions
- Collaborate with quant researchers, risk, IT, and operations teams to deliver robust and scalable quantitative infrastructure across the investment platform
- Contribute to building a best-in-class, data-driven investment technology platform supporting both fixed income and alternative strategies
- Support the production environment of quantitative tools used by the investment team, ensuring reliability, transparency, and operational efficiency
Skills And Qualifications
- 10+ years of experience in quantitative engineering, financial engineering, or front-office technology within asset management, hedge funds, financial institutions or other similarly data-driven entity
- Strong hands-on Python programming skills, including production-quality analytics and data processing frameworks
- Experience working with financial market data vendors such as Bloomberg, ICE, FactSet, Kamakura, LSEG, or similar large financial datasets
- Deep experience in data ingestion, normalization, and large-scale data processing, preferably in financial markets environments
- Solid understanding of fixed income and credit markets, including bonds, credit risk metrics, and portfolio analytics preferred
- Experience designing and implementing portfolio optimization or simulation frameworks preferred
- Track record building front-office quantitative tools used by portfolio managers or traders
- Familiarity with REST APIs and backend service development for internal applications and analytics platforms
- Proven ability to collaborate with quant researchers, portfolio managers, risk teams, and technology groups in complex data-rich environments
- Strong analytical, problem-solving, and engineering skills with the ability to translate business requirements into scalable technical solutions
- Excellent communication skills — able to convey complex quantitative and technical concepts to investment professionals
- Strong team player comfortable working across investment, research, and technology teams in a fast-paced environment
Education
- Master’s or Ph.D., or equivalent work experience, in a quantitative discip