[Hiring] Lead Software Engineer @eLEND

Role Description

The Lead Software Engineer, AI Enablement is a senior, hands-on individual contributor providing shared technical leadership across the Alpha and Delta teams. This role operates at the intersection of software engineering, architecture, modernization, AI enablement, and customer experience.

Key Responsibilities

• Provide hands-on technical leadership across the Alpha and Delta teams, supporting new product development, platform modernization, production support, technical debt reduction, and system reliability.
• Design, build, test, deploy, and troubleshoot production software across frontend, backend, integrations, databases, and cloud components.
• Help define application architecture, integration patterns, coding standards, development practices, and reusable engineering approaches.
• Build reusable services, APIs, libraries, development templates, components, and automation that can be leveraged across teams.
• Evaluate technical solutions and communicate tradeoffs related to speed, scalability, security, cost, maintainability, and customer impact.
• Mentor engineers, facilitate technical discussions, and elevate engineering standards without direct people-management responsibility.
• Help design and deliver new products, features, integrations, and digital customer experiences.
• Establish technical patterns that enable teams to release smaller increments more frequently and safely.
• Build modular, API-first, observable, testable solutions designed to evolve with business and customer needs.
• Translate customer and business needs into software that reduces friction, simplifies workflows, minimizes unnecessary data entry, and creates more responsive digital interactions.
• Enable controlled pilots, prototypes, feature flags, and rapid feedback loops while maintaining production stability.
• Improve the reliability, performance, security, and supportability of business-critical applications.
• Modernize legacy systems through practical approaches including refactoring, service decomposition, API enablement, automation, and replacement of obsolete components.
• Identify and prioritize technical debt based on customer impact, operational risk, engineering effort, and business value.
• Lead technical investigation and resolution of production incidents, recurring defects, performance issues, and escalated customer-impacting issues.
• Strengthen logging, monitoring, alerting, deployment validation, rollback procedures, technical documentation, and production support practices.
• Identify and implement practical uses of AI that reduce the time required to design, build, test, document, review, and release software.
• Establish approved patterns for AI-assisted development across requirements analysis, code generation, refactoring, debugging, testing, and documentation.
• Automate repetitive engineering activities such as unit-test generation, regression testing, code documentation, dependency analysis, defect triage, release-note preparation, and technical-debt identification.
• Use AI-assisted analysis to identify defects, security vulnerabilities, performance concerns, inconsistent patterns, and maintainability issues earlier in the development lifecycle.
• Develop AI-enabled approaches to improve test-case creation, test coverage, defect detection, and validation of customer-facing workflows.
• Integrate AI-supported quality checks and automated validation into CI/CD pipelines to improve release confidence.
• Establish practical metrics to measure AI's impact on cycle time, deployment frequency, defect rates, test coverage, release stability, and developer productivity.
• Create reusable prompts, templates, development standards, contextual documentation, and automated workflows that allow engineers to use AI consistently and effectively.
• Maintain engineering accountability by ensuring engineers review, test, secure, and approve AI-generated code and technical outputs.
• Protect company information, intellectual property, source code, borrower information, and sensitive data through appropriate AI development practices and approved access controls.
• Help design digital experiences that use AI to make customer and partner interactions faster, simpler, and more intuitive.
• Apply AI to summarize information, guide users, prepopulate data, surface next actions, explain requirements, and reduce unnecessary navigation.
• Support conversational experiences, including chat, voice, and agent-assisted capabilities when they create meaningful customer or business value.
• Integrate AI capabilities securely into eLEND's existing digital products rather than relying on disconnected tools.
• Build appropriate controls around customer-facing AI, including validation, traceability, fallback behavior, access controls, and human review.
• Focus AI development on measurable outcomes such as faster task completion, fewer customer handoffs, reduced data-entry effort, improved response times, and higher digital completion rates.
• Develop and review high-quality, scalable code for Angular and .NET applications.
• Conduct code reviews focused on correctness, security, maintainability, performance, and testability.
• Establish and reinforce design patterns, coding conventions, testing expectations, security practices, and technical documentation standards.
• Strengthen CI/CD pipelines, automated testing, code-quality controls, deployment automation, environment consistency, release validation, and rollback capabilities.
• Use telemetry, profiling, debugging, and monitoring tools to identify and resolve application, API, database, and integration bottlenecks.
• Partner with Quality Assurance to incorporate unit, integration, regression, performance, and security testing throughout the development lifecycle.
• Identify dependencies, surface technical risks, estimate complex work, and help teams break initiatives into achievable delivery increments.
• Maintain architecture diagrams, technical designs, decision records, API documentation, runbooks, and knowledge-transfer materials.
• Partner closely with Product Management, Technology Product Managers, Quality Assurance, Security, Infrastructure, Data, and business stakeholders.
• Continuously evaluate systems and engineering practices and implement improvements that increase delivery speed, platform reliability, and customer value.

Qualifications

• Advanced proficiency in C#, .NET, ASP.NET Core, and secure, scalable web applications, background services, and APIs.
• Strong experience with modern frontend development using Angular and TypeScript.
• Proficiency with Azure SQL Server, including schema design, indexing, query optimization, and performance troubleshooting.
• Experience designing RESTful APIs, service-oriented architectures, event-driven applications, and scalable microservices.
• Strong understanding of distributed-system concepts including asynchronous processing, resiliency, idempotency, fault handling, caching, and eventual consistency.
• Ability to modernize applications incrementally while maintaining business continuity.
• Ability to create and communicate architecture diagrams, technical designs, interface specifications, and architectural decision records.
• Strong knowledge of Microsoft Azure services including App Services, Function Apps, Service Bus, Event Grid, Key Vault, Azure SQL, storage, monitoring, and identity services.
• Experience with CI/CD pipelines, automated testing, deployment automation, release controls, and environment management using Azure DevOps or comparable platforms.
• Advanced Git skills, including branching strategies, pull requests, release management, and working within complex shared codebases.
• Experience with unit and integration testing frameworks such as xUnit, NUnit, or MSTest.
• Strong application-security knowledge, including OAuth 2.0, OpenID Connect, SSO, managed identities, RBAC, secure key management, and secure API design.
• Ability to diagnose and optimize distributed applications through logging, monitoring, profiling, debugging, and performance analysis.
• Hands-on experience using AI-assisted software development tools for coding, testing, debugging, refactoring, documentation, or code review.
• Experience integrating AI models or services into enterprise applications through APIs or SDKs.
• Understanding of how to provide AI tools with appropriate codebase, architecture, requirements, and application context.
• Ability to develop reusable prompts, engineering workflows, guardrails, and development standards for AI-assisted software delivery.
• Familiarity with AI-supported test generation, code analysis, defect detection, documentation, and release automation.
• Understanding of risks associated with AI-generated code, including insecure patterns, incorrect logic, intellectual-property concerns, sensitive-data exposure, and insufficient validation.
• Ability to evaluate AI development tools based on measurable improvements to software delivery rather than novelty alone.
• Understanding of customer-facing AI patterns including conversational interfaces, intelligent guidance, information summarization, workflow assistance, and human-in-the-loop interactions.
• Ability to determine when a problem should be solved through AI, traditional software, workflow automation, business rules, or a combination of approaches.
• Demonstrated ability to provide technical leadership across multiple teams as a senior individual contributor.
• Strong mentoring mindset and a record of improving engineers' technical judgment, code quality, and independence.
• Ability to influence technical direction without direct reporting authority.
• Experience modernizing business-critical applications while maintaining operational continuity.
• Strong analytical and problem-solving skills, particularly when addressing ambiguous, cross-system, or production-critical issues.
• Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
• Ability to balance delivery speed with security, quality, maintainability, customer experience, and long-term platform health.

Benefits

• Competitive base pay: $184,200k-$230,250k
• Comprehensive medical, dental, and vision coverage
• 401(k) plan with company participation
• Paid time off and company holidays
• Professional development and career growth opportunities
• Access to tools, systems, and resources that support operational and client success
• Collaborative and growth-oriented team environment

Worksite

• Remote
• Senior individual contributor role supporting both the Alpha and Delta teams.
• Reports to the SVP, APEX.
• Cross-functional collaboration with Product, Technology Product Management, QA, Security, Infrastructure, Data, and business stakeholders.
• Regular collaboration through technical discussions, architecture reviews, code reviews, development workflows, and production support.
• This position does not include direct people-management responsibilities.
• The role requires the ability to work across multiple teams and influence technical direction through expertise, architecture, delivery, mentoring, and technical judgment.

Equal Opportunity for All

At eLEND, we are committed to building a diverse and inclusive workplace where all team members are respected, supported, and empowered to succeed. Employment decisions are based on qualifications, experience, and business needs, ensuring equitable opportunities for all individuals regardless of background or identity.

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Join today to connect with our team, stay informed about upcoming roles, and explore how your technical expertise, engineering leadership, and passion for practical AI can help shape the future of technology and home lending at eLEND.