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Our client is a premier global asset management organization with more than 85 years of experience. The firm provides investment solutions and a broad range of equity, fixed income, and multi-asset capabilities to individuals, advisors, institutions, and retirement plan sponsors. It takes an active, independent approach to investing, offering a dynamic perspective and meaningful partnership to help clients navigate an evolving financial landscape with confidence.
The organization believes doing the right thing for clients and employees is good business. Employees have opportunities to create meaningful impact while benefiting from career development resources, competitive compensation, comprehensive benefits, and flexible work arrangements. The culture is collaborative, inclusive, and built on mutual respect, innovation, and generosity.
Join an organization where you'll have the opportunity to grow your career while making a meaningful impact.
Lead the design, development, and deployment of production-grade agentic AI systems embedded directly into the investment lifecycle as part of the Investments Technology team.
Work in cross-functional squads across Investments, Investments Technology, and innovation teams to architect, build, and operationalize autonomous AI agents that interact with proprietary financial data, enterprise systems, and investment professionals. AI agents will encompass investment research, quantitative analysis, portfolio management, and trading business functions.
Help define the technical standards, architectural patterns, governance frameworks, and engineering discipline required to scale AI responsibly across a global asset management platform.
This role offers a hybrid work schedule with the opportunity to split onsite time between Baltimore, MD and Washington, DC.
Lead the design, development, and deployment of AI systems, providing technical mentorship and oversight to engineering squads.
Collaborate in cross-functional squads to ensure responsible AI solutions are scaled across the enterprise.
Partner with business stakeholders to develop agent-driven workflows that automate complex processes and generate actionable insights.
Champion engineering excellence by establishing and enforcing best practices in AI development, continuous integration, and code quality.
Oversee projects on agent orchestration, prompt engineering, and real-time, data-driven automation.
Prioritize and manage technical debt, driving ongoing improvements in AI platforms and infrastructure.
Proactively identify and pursue opportunities to apply AI agents for increased business value and operational efficiency.
Engage directly with business stakeholders to thoroughly understand organizational needs, strategic priorities, and evolving market demands.
Make informed technology decisions that align with the firm's long-term strategy, organizational objectives, and fiscal responsibility.
Leverage deep business knowledge to translate complex requirements into robust, scalable technology solutions that drive measurable business value.
BS or MS in Computer Science or a related technical field (or equivalent experience), with 8+ years of progressive professional development experience in object-oriented languages (such as Java, Python, or JavaScript), including demonstrated leadership of engineering teams.
Extensive hands-on expertise in architecting and delivering cloud-native solutions using AWS or Azure, containerized microservices, and agent frameworks.
Exceptional analytical and problem-solving skills, with a proven ability to guide teams through complex technical challenges.
Ability to communicate with and influence both business stakeholders and technical teams.
Demonstrated commitment to engineering excellence through setting and upholding standards for automated testing, code reviews, and continuous delivery.
Results-oriented leader with a passion for mentoring others, fostering innovation, and staying at the forefront of emerging technologies.
Hands-on experience building LLM-powered or agent-based systems in production.
Experience with retrieval-augmented generation (RAG), vector databases, MCP servers, agent orchestration frameworks, prompt evaluation and iteration, model benchmarking, and performance testing.
Experience with Amazon Bedrock AgentCore, AWS Kiro, and OpenAI Codex.
Experience in asset management, financial markets, or quantitative research environments.
Solid understanding of financial markets, financial instruments, and financial datasets.
Client licenses are not required and will not be supported for this role.
This role is eligible for hybrid work, with up to three days per week from home.