Senior Software Engineer, Technical Lead

We believe that by equipping researchers with rapid insights and providers with tailored, on-demand data, we can help people lead better, healthier lives. At Digital Infuzion, we harness innovative healthcare solutions and cutting-edge bioinformatics to make meaningful impacts in patient care. Our team thrives in a creative, open, and growth-oriented environment, guided by our core values:

• Outcomes First: Focusing on what matters most and making timely, informed decisions.
• Innovative: Embracing creativity and continuous improvement to drive novel solutions.
• Radical Candor: Communicating openly and honestly, balancing direct feedback with genuine care.
• Never Satisfied: Pursuing excellence and continuous growth beyond the status quo.
• Resilient: Adapting and persevering through challenges, turning obstacles into opportunities.

If you’re passionate about leveraging technology to improve healthcare and want to work in an environment that values innovation and collaboration, we may have just the opportunity for you., The Senior Software Engineer / Technical Lead provides hands-on technical leadership for developers across two teams supporting multiple projects. This role is accountable for cross-project systems architecture, production delivery, cloud operations, engineering quality, and technical direction while remaining actively engaged in implementation and code reviews.The position translates product and scientific needs into secure, reliable, maintainable systems; makes and documents consequential technical decisions; and communicates tradeoffs and risks to technical and nontechnical stakeholders. This is a technical leadership role with the potential for direct people-management responsibilities. AI-assisted engineering and AI-enabled capabilities may be used where appropriate, but the Technical Lead retains accountability for architecture, code quality, security, privacy, and production outcomes., * Design, implement, test, deploy, and maintain high-value production capabilities, particularly in high-risk or cross-cutting areas.

• Define and maintain systems architecture across projects, including service boundaries, data flows, interfaces, integration patterns, non-functional requirements, technical roadmaps, documented decisions, and technical debt.

• Translate product and scientific needs into executable technical specifications and delivery plans; identify technical risks and use focused discovery when additional learning is needed.

• Establish engineering standards for code review, testing, CI/CD, documentation, refactoring, and maintainability; review high-risk changes and ensure AI-generated work meets the same standards as human-written code.

• Own cloud platform direction, primarily in our AWS environment, including service selection, infrastructure as code, deployment practices, observability, reliability, security, recovery, performance, and cost awareness.

• Provide technical leadership during production incidents; coordinate diagnosis and recovery, lead root cause analysis, and ensure corrective actions improve the underlying platform.

• Evaluate and guide AI-enabled solutions when appropriate, including model, provider, retrieval, integration, evaluation, privacy, security, observability, fallback, performance, and cost considerations.

• Mentor and coordinate developers across two teams through technical planning, delegation, code review, actionable feedback, and resolution of technical disagreements.

• Identify recurring delivery, operational, and quality gaps; implement practical improvements and automation; and verify that changes improve outcomes.

• Communicate architecture, technical tradeoffs, risk, uncertainty, and investment needs clearly to technical and nontechnical stakeholders.

• Typically 10+ years of experience building and operating production software, or equivalent demonstrated experience with comparable ownership of systems and outcomes.

• Deep expertise in at least one modern programming language, such as C++, TypeScript/JavaScript, Python, Rust, or a comparable language, with the ability to evaluate unfamiliar code, frameworks, and designs across the stack.

• Demonstrated experience taking production capabilities from ambiguous requirements through design, implementation, deployment, and reliable operation.

• Demonstrated ownership of systems architecture across more than one project or team, including service boundaries, interfaces, data models, security and reliability requirements, migration paths, and technical debt.

• Hands-on experience selecting and configuring cloud services, defining infrastructure as code, deploying workloads, diagnosing failures, and operating production platforms.

• Strong software design, testing, code-review, CI/CD, debugging, incident-response, observability, and root-cause-analysis practices.

• Experience leading technical planning, prioritization, delegation, mentoring, feedback, and difficult technical tradeoffs for multiple developers or teams. Formal line-management experience is not required.

• Substantial recent experience using AI-assisted engineering tools, with demonstrated judgment in providing effective context, challenging generated designs, and independently validating code and architecture.

• Strong written and verbal communication skills, including the ability to explain complex technical decisions and uncertainty to varied audiences.

• Demonstrated ability to identify delivery or operational inefficiencies, implement practical improvements, and assess whether those changes improved results.

Preferred Qualifications

• AWS experience and hands-on use of Terraform, CloudFormation, or comparable infrastructure-as-code tools.

• Experience designing organization-level testing strategies or CI/CD pipelines.

• Experience designing relational or NoSQL data models, scientific data-ingestion systems, or data-validation platforms.

• Experience building scientific, analytical, or data-rich interfaces using visualization libraries such as D3.js or Three.js.

• Experience integrating AI or model-backed capabilities and addressing evaluation, data handling, privacy, security, failure modes, observability, fallback behavior, performance, and cost.

• Experience with data preparation, model evaluation, retrieval-augmented generation, model deployment, deep learning, or related AI/ML platforms.

• Experience leading effectively in self-directed, small-team environments with limited handoffs between engineering and operations.

• Interest in biomedical research, particularly infectious diseases.

*This is a hybrid remote-eligible position