Technology R&D Senior Engineer

TruStage

17h•$111,800 - $167,700

About The Position

At TruStage, we’re on a mission to make a brighter financial future accessible to everyone. We put people first, and work hand in hand with employees and customers to create a diverse and inclusive environment. Passionate about building insurance and financial services solutions, we push the boundaries of what’s possible. We need you to help us shape what’s next. You’ll be encouraged to share your experiences, ideas and skills to help others take control of their financial future. Join a team that has received numerous awards for being a top place to work: TruStage awards and recognition Job Summary: The Senior, Technology R&D Engineer researches, builds, tests, and delivers working prototypes and proof-of-concepts that turn emerging technologies into practical enterprise solutions. Working within the Technology Innovation Office, this role investigates business problems, designs technical experiments, builds solutions, and validates outcomes through hands-on engineering execution. The role starts with business problems and applies emerging or mature technology to create measurable value through rapid prototyping, practical experimentation, and pilot-ready solution development.

Requirements

Bachelor’s degree in computer science, engineering, related technical field, or equivalent experience
5+ years of software engineering, prototyping, or technical development experience
Hands-on experience with modern development tools, programming languages, and cloud platforms, including examples such as React, Next.js, Python, Node.js, C#/.NET, REST APIs, and relational databases
Hands-on full-stack capability with depth in at least one area across frontend frameworks, backend languages/frameworks, APIs, databases, and integration patterns
Proficiency with Git, CI/CD concepts, and collaborative development workflows
Ability and willingness to use AI-assisted development tools for code generation, pair programming, testing, and debugging as a regular part of the engineering workflow
Understanding of data modeling, SQL, structured and unstructured data, and basic data pipeline concepts
Working knowledge of or willingness to learn Azure, Azure AI, Microsoft Fabric, and related Microsoft tools; familiarity with AWS or GCP is a plus
Hands-on exposure to AI, automation, or emerging technologies preferred
Strong analytical and problem-solving skills
Ability to learn quickly and operate in ambiguous, exploratory environments
Curiosity, initiative, self-direction, and problem-first orientation
Strong collaboration and communication skills
Awareness of data privacy, model governance, AI ethics, compliance, and regulated-industry constraints
Experience working in or building technology for regulated industries such as insurance, financial services, or healthcare preferred

Nice To Haves

graph databases
knowledge graphs
network analysis
applied analytics
open-source contributions
technical writing
innovation-team experience

Responsibilities

Work directly with engineers, data scientists, and analysts across the Technology Innovation Office to deliver R&D outcomes
Drive technical discovery conversations and convert business needs into executable innovation work
Engage technology, compliance, risk, product, and platform teams to clarify constraints and shape practical solution paths
Recommend R&D priorities, backlog focus, and problems worth solving based on feasibility, impact, and measurable value
Coordinate work across asynchronous contributors and varied working styles to keep experiments moving forward
Research emerging technologies, tools, and approaches aligned to enterprise innovation priorities
Build technical solutions across multiple R&D initiatives
Design, develop, test, and iterate prototypes and proof-of-concepts with appropriate technical direction from other engineers and technical subject matter experts
Perform data integration, modeling, and pattern discovery using enterprise data
Iterate quickly, apply learning from outcomes, and advance rapid experimentation into usable technical artifacts
Conduct structured evaluations of AI platforms, frontier models, data tools, and vendors
Assess Microsoft ecosystem options first, then alternatives when appropriate
Run experiments to assess feasibility, performance, and applicability of new technologies
Refine evaluation frameworks and methods based on experiment results and stakeholder needs
Collect, analyze, and document results against success criteria
Determine solution viability and readiness for additional development, pilot use, or retirement
Write, test, debug, and maintain code and technical artifacts that support R&D efforts
Build for scalability, maintainability, and operational supportability
Follow engineering, security, and governance standards
Conduct and contribute to code reviews, design discussions, and retrospectives
Integrate prototype solutions into pilot environments
Prepare prototypes for pilot transition, outcome measurement, and production handoff
Create clear technical documentation for solution approaches, architecture decisions, findings, and outcomes
Distill research findings into concise summaries and recommendations
Document compliance, governance, and review needs for production readiness
Produce reusable knowledge assets for R&D, AI, Automation, and Innovation Enablement teams