Technology R&D Lead Engineer

TruStage

17h•$125,100 - $187,700•Hybrid

About The Position

The Lead, Technology R&D Engineer leads the design, development, and validation of emerging technology solutions, translating research into scalable prototypes and pilot-ready capabilities. This role drives technical execution across the R&D lifecycle, from experimentation through pilot deployment, ensuring solutions are feasible, valuable, and aligned to enterprise strategy. The Lead Engineer partners across AI, Automation, and Innovation Enablement teams to accelerate the transition of R&D outputs into business impact. The role starts with enterprise problems, not product demos, and applies emerging or mature technology where it can unlock measurable business value.

Requirements

Bachelor’s degree in computer science, engineering, or related technical field, or equivalent combination of education and/or related professional work experience
7 years of experience in software engineering, product development, or emerging technology roles
Demonstrated experience developing prototypes, proofs-of-concept, pilot solutions, or production-ready capabilities
Hands-on full-stack development experience sufficient to build working prototypes independently, including modern frontend frameworks, backend development, REST or GraphQL APIs, and relational and non-relational databases
Strong experience with modern development frameworks, cloud platforms, system architecture, Git, CI/CD concepts, and collaborative development workflows
Strong familiarity with the Microsoft technology ecosystem, including Azure cloud services, Azure AI, Azure OpenAI Service, Microsoft Fabric, Power Platform, and related tooling
Experience assessing Microsoft-native solutions, external alternatives, vendor offerings, build-vs-buy options, platform evaluations, or technology strategy work against business and technical requirements
Familiarity with AI/ML, automation, data-driven systems, and AI-assisted development tools for code generation, pair programming, testing, debugging, and technical analysis
Direct experience working with data across multiple enterprise systems
Experience operating in regulated environments preferred, with strong awareness of privacy, model governance, AI ethics, compliance, risk, auditability, and data governance expectations
Proven ability to work across technical and business teams to deliver outcomes, support operational handoff, and partner with engineering, product, or platform teams
Demonstrated experience mentoring engineers, researchers, or early-career technologists through code reviews, design discussions, and technical coaching
Strong communication skills with the ability to translate technical insights, decisions, risks, and tradeoffs into business value
Strong analytical, problem-solving, and decision-making skills
Strong problem-first thinking, curiosity, self-direction, and comfort with ambiguity

Nice To Haves

exposure to graph databases, knowledge graphs, network analysis, applied analytics, open-source contributions, technical writing, or innovation-focused team environments

Responsibilities

Lead the design and development of prototypes, proofs-of-concept, and pilot solutions
Build full-stack prototypes independently when needed
Translate research objectives into scalable technical architectures and implementation approaches
Design with scalability, supportability, and integration patterns in mind
Ensure solutions are technically sound, secure, and aligned with enterprise architecture
Identify high-impact problems and make the case for R&D investment
Evaluate emerging technologies for business applicability and integration potential
Evaluate mature technologies applied in new ways, not only emerging tools
Lead build-vs-buy analysis, vendor assessments, and platform evaluations
Contribute to shaping the R&D pipeline and prioritization of opportunities
Align technical exploration to enterprise strategy and innovation objectives
Decompose ambiguous business challenges into data questions, technology hypotheses, and prototype plans
Define experiment design, success criteria, and evaluation frameworks
Lead technical validation of emerging technologies, identifying strengths, risks, and limitations
Synthesize findings into clear recommendations on whether to advance, pivot, or discontinue initiatives
Use AI-assisted development tools as a natural part of daily engineering workflow
Embed AI/ML capabilities into prototypes and pilot solutions where appropriate
Support outcome measurement and production handoff planning for successful pilots
Engage compliance, risk, legal, and information security early in solution development
Lead the transition of successful prototypes into pilot implementations
Partner with engineering, product, and platform teams to support scaling into production environments
Ensure alignment with governance, compliance, and operational requirements
Provide technical leadership across R&D initiatives, guiding design and development decisions
Set technical direction and create effective code review practices
Mentor and coach Engineers to enhance technical capability, execution quality, independent problem-solving, and sound technical judgment
Mentor across experience levels and working styles, including asynchronous collaboration
Establish best practices for experimentation, rapid prototyping, and iterative development
Communicate technical findings, insights, and tradeoffs to both technical and business stakeholders
Explain technology decisions through business outcomes, risks, and tradeoffs
Support decision-making by translating complex concepts into actionable recommendations