• Directly manage Software Engineering Team Leads across the Business Productivity, Engineering Tools, and AI Tools teams, providing day-to-day guidance, technical direction, and performance oversight. • Hold regular one-on-ones and team reviews to assess team health, remove blockers, and ensure each team is operating at a high level of efficiency and morale. • Foster a culture of engineering excellence, continuous improvement, psychological safety, and accountability across all software development teams. • Partner with the Director of Tech Talent & People Operations on staffing plans, hiring pipelines, and workforce strategy for engineering teams; collaborate on career track development, role leveling, and succession planning. • Work closely with the Director of AI Strategy & Enablement to align engineering team capabilities and delivery roadmaps with DLB’s AI implementation goals, ensuring teams are equipped to build and maintain AI-powered solutions. • Coordinate with the Director of Solution Delivery & Client Success to translate project requirements and client feedback into engineering priorities, maintain realistic delivery timelines, and ensure client-facing commitments are met. • Establish team-level and individual performance goals aligned to departmental and organizational objectives; conduct regular performance reviews and provide structured, actionable feedback. • Define and track engineering KPIs – including delivery velocity, code quality, system reliability, and team capacity – and use these metrics to drive informed decisions and surface risks early. • Champion career development for engineering staff by identifying growth opportunities, supporting skill-building initiatives, and creating clear paths for advancement in partnership with People Operations. • Define and enforce coding standards, architectural patterns, and development best practices across all software teams to ensure high-quality, maintainable, and secure codebases. • Own the technical roadmap for the software engineering function, balancing short-term delivery demands with long-term architectural health and platform scalability. • Evaluate and introduce new tools, frameworks, and methodologies – including AI-assisted development tooling – that improve team productivity and output quality. • Oversee end-to-end engineering delivery across active projects, ensuring teams are focused, unblocked, and executing against committed timelines and scope. • Manage resource allocation across teams, anticipate capacity constraints, and make proactive adjustments to sustain reliable delivery across the portfolio. • Maintain visibility into project health across all teams and escalate risks or issues to executive leadership with recommended paths to resolution.

Join our network of independent alteration professionals specializing in evening and cocktail wear. What You'll Do • Alter evening gowns, cocktail dresses, and gala/black-tie dresses (hemming, bodice/waist, straps, cups, zippers) • Work with structured formal dresses (multiple layers, lace, beading, sequins, linings) • Conduct fittings, take precise measurements, and communicate timelines clearly • Deliver high-quality finishing and maintain an organized workspace suitable for fittings We also receive requests for wedding dresses, prom dresses, bridesmaid dresses, suits, and other formalwear. Requirements • Experience with women's formalwear and/or evening wear alterations • Strong garment construction knowledge + precision measuring • Machine + hand sewing proficiency • Professional communication and customer service Benefits / Highlights • Work from home (independent contractor role) • Local client requests provided through the platform • Flexibility to accept the jobs that fit your schedule • Opportunity to grow repeat clients and reviews through your profile

• Build scalable APIs and microservices architecture • Design and develop efficient, compatible, and secure custom software applications to deliver complete and highly reliable software and improve end-user experience. • Lead teams of developers by determining which tools, APIs, design patterns and best practices to use. • Design and implement microservices-based solutions, following domain-driven design (DDD) principles to create modular and flexible systems. • Leverage your experience in Javascript to work on both frontend and backend components as needed. • Apply software design principles and UML methodology to create well-structured, maintainable, and scalable code. • Provide technology architectural assessments, strategies, and roadmaps for one or more technology domains. • Define and implement standard processes and procedures for managing data integration and data exchange models between systems on premise and cloud systems including security, traceability, audit, performance, and risk. • Work with delivery team to understand functional requirements and interact with other cross-functional teams to architect, design, develop, test, and release features. • Provide constructive feedback of source code during code reviews. • Perform other duties and/or special projects as assigned. • Developing and maintaining all server-side network components. • Ensuring optimal performance of the central database and responsiveness to front-end requests. • Collaborating with front-end developers on the integration of elements. • Designing customer-facing UI and back-end services for various business processes. • Developing high-performance applications by writing testable, reusable, and efficient code.

Job Title: AI Product Engineer (Full Stack) Position Type: Full-Time, Remote Working Hours: U.S. Business Hours About the Role We’re hiring an execution-focused AI Product Engineer (Full Stack) to build and scale a production-ready web application from the ground up. This is a hands-on role for someone who can take full ownership of both frontend and backend development while integrating AI capabilities into real-world product use cases. This is not a support or maintenance role — it requires building, shipping, and iterating on a live product with strong system design, performance, and reliability. What You’ll Own Full Product Development (End-to-End) - Build and launch a production-ready web application from concept to deployment. - Own both frontend and backend development across the full stack. - Continuously iterate and improve the product post-launch. AI Integration & Workflows - Design and implement AI-driven workflows within the product. - Integrate LLMs (e.g., Claude or similar) into real use cases. - Implement guardrails to manage AI limitations (hallucinations, edge cases). Backend Systems & Infrastructure - Build and manage backend systems using Supabase or similar tools. - Design scalable APIs and data structures. - Ensure efficient data handling and system performance. Security & System Reliability - Implement authentication, permissions, and data protection practices. - Ensure system security and integrity across the platform. - Optimize performance, scalability, and reliability. Product Collaboration & Iteration - Work closely with leadership to rapidly ship and improve features. - Translate product ideas into working technical solutions. - Continuously refine the system based on feedback and usage. Debugging & Optimization - Identify and fix system issues and bugs. - Improve system stability and user experience. - Maintain high-quality code and system performance. Must-Have Experience & Skills Non-Negotiables - Strong full stack development experience (frontend + backend). - Proven track record of building and shipping real, production-level products. - Hands-on experience integrating AI/LLMs into applications. - Strong understanding of system architecture and API design. - Experience with Supabase or similar backend platforms. - Strong understanding of AI limitations (hallucinations, failure handling). - Knowledge of security best practices (authentication, permissions, data protection). - Ability to work independently and take full ownership of product development. Nice-to-Haves - Experience building AI agents or automation workflows. - Familiarity with Claude or similar LLM tools in production. - Experience building SaaS or operational platforms. - Exposure to aviation, logistics, or membership systems. - Experience scaling products from MVP to production. Key Metrics for Success - Successful launch of production-ready application. - Stability and performance of the system. - Quality and effectiveness of AI integrations. - Speed of feature delivery and iteration. - Reduction in bugs and system issues over time. - Scalability and maintainability of the platform. Interview Process - Initial Screening Call - Technical & Systems Design Interview - Practical Task (Product Build / AI Integration Scenario) - Final Interview - Internal Review & Approval - Offer & Onboarding #LI-AG1