Senior Solutions Engineer, Software - Investments Technology

Note: This role has a required hybrid work arrangement in our Boston, MA office.

Hiring Manager: Patricia Tangney

The Senior Solutions Engineer, Software is the pinnacle of the engineering craft within the domain. The role sets the engineering standard across Global Liquid Markets, Risk Management & Compliance, and Global Strategy & Capital Allocation, leads the adoption of AI and agent-based engineering across the

full software development lifecycle, and deploys AI directly to solve investment business needs. It defines how AI is built into LMI's investment systems — from architecture decisions to engineering, testing, and delivery practices across the full SDLC — and is expected to think and act at the level

of the whole portfolio rather than any single system or team. Provides technical oversight and engineering solutions to the most complex and strategic system and application development initiatives across the domain portfolio, developing clear, comprehensive, and integrated system, technical, and product recommendations that support business plans and long-term investment strategies. Oversees design reviews and engineering frameworks across multiple product teams and, working closely with Architects, Solutions Engineers, and Embedded Tactical Engineers, establishes and drives adoption of architecture and engineering standards — CI/CD, automated testing, infrastructure-as-code,

and shared conventions — to promote operational excellence, security, reliability, performance efficiency, and cost optimization as operating norms.

Works in close collaboration with Embedded Tactical Engineers and domain engineering teams; LMI's emphasis on face-to-face partnership is central to how this role operates and how its impact is felt. Shapes the multi-year engineering strategy for the domain, originates and drives broad cross-team initiatives, and is recognized across LMI Technology as the authority on how AI-native, investment-grade systems are designed and built. Deep knowledge of investment management — how liquid markets, risk management, and capital allocation functions operate, make decisions, and use technology — is essential. A thought leader who influences senior leadership and advances the craft of engineering across the organization.

Responsibilities:

• Leads the domain's AI and agent engineering agenda. Architects AI-native solutions, drives agent-based approaches throughout the SDLC —requirements, design, code generation, testing, deployment, and operations — and deploys AI to solve investment business problems directly across GLM, Risk & Compliance, and GSCA. Sets the standard for AI engineering practice across LMI Technology and ensures the domain operates at the frontier of what modern engineering can deliver in a regulated investment environment.
• Promotes and scales AI adoption across engineering. Actively champions the use of AI and agents by every engineer in the domain — defining the patterns, tooling, guardrails, and evaluation practices that make AI-assisted engineering safe and productive, measuring adoption and impact, and removing the barriers that keep teams from using it.
• Establishes and drives engineering practices and guardrails. Defines and leads engineering excellence guardrails across the domain — coding standards and conventions, design and review practices, API contracts, and documentation — and ensures they are adopted consistently rather than left to individual teams.
• Champions CI/CD, testing, and automation as the default.
  • Drives fully automated build, test, and deployment pipelines; establishes automated unit, integration, contract, and regression testing as a condition of delivery; and promotes infrastructure-as-code, observability, and automated operations so that manual toil is eliminated and change is safe, repeatable, and fast.
  • Develops clear, comprehensive, and integrated system, technical, and product recommendations that ensure consistency, security, maintainability, and flexibility within the GLM, Risk & Compliance, and GSCA domain portfolio.
  • Provides consultation to technology leaders, investment business partners, and peer groups on long- and short-range product features.
  • Provides oversight at the portfolio level, influencing decision-making and prioritizing the engineering backlog across domain programs and teams.
• Partners daily with Embedded Tactical Engineers — providing technical direction, design review, and the domain knowledge that makes their delivery effective. This collaboration is primarily in-person and is central to how the domain raises its engineering capability over time.
  • Contributes to forecasts of business and technology trends to define technical direction within the domain portfolio, aligned with LMI's investment strategy and the evolving capabilities of AI and agent-based systems; balances the long-term big picture with the short-term implications of decisions.
  • Educates and drives adoption of the well-architected framework — operational excellence, security, reliability, performance efficiency, and cost optimization — as cultural norms, and recommends process improvements with an emphasis on where AI and automation can eliminate friction.
  • Participates in incident management events, provides consultative recommendations on viable resolutions, and drives root-cause remediation and preventive automation.
  • Maintains collaborative and strategic partnerships with investment business stakeholders, vendors, product owners, and technology teams across the domain; mentors staff with particular focus on growing the Embedded Tactical Engineer cohort and building AI engineering fluency.
  • Shares expertise so teams continuously improve and learn together, demonstrated through publication, speaking engagements, or other indicators of external industry recognition.