Principal Engineer

Job Summary Responsibilities

• Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups
• Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking
• Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions
• Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions
• Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization
• Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership

Required Qualifications

• 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications 1. Consumer Platform Architecture

• Lead architecture for high-scale consumer applications serving millions of users.
• Design systems optimized for:
• Low latency high throughput
• Global distribution edge delivery
• Seamless user experience (UX)
• Define architecture patterns for:
• Personalization engines
• Recommendation systems
• Real-time engagement platforms
• Ensure alignment with privacy, security, and compliance (GDPR, etc.).

2. Core Engineering (Java Python at Scale)

• Architect and build distributed services using:
• Java (Spring Boot, reactive frameworks)
• Python (FastAPI, ML services)
• Drive standardization of APIs, SDKs, and shared platform services.
• Enable reusable platform capabilities for rapid product innovation.
• Solve complex challenges in concurrency, caching, and distributed data management.

3. AI/ML LLM-Driven Consumer Experiences

• Design AI-powered features such as:
• Recommendations personalization
• Conversational interfaces (chatbots, assistants)
• Content generation and summarization
• Build and scale LLM-based systems (RAG pipelines, prompt orchestration, agentic flows).
• Integrate with vector databases, embeddings, and real-time inference APIs.
• Ensure safe and responsible AI usage in consumer scenarios (bias, hallucination, privacy).

4. System Design Distributed Architecture

• Architect robust systems using:
• Microservices, serverless, event-driven patterns
• Streaming platforms (Kafka, Event Hub, etc.)
• Design for:
• Horizontal scalability
• Fault isolation
• Graceful degradation
• Evaluate trade-offs across consistency, availability, and performance.

5. SDLC Platform Engineering Excellence

• Define modern SDLC practices for high-velocity consumer product teams.
• Drive:
• CI/CD automation
• Blue-green canary deployments
• Feature flag-driven releases
• Establish developer platforms for productivity and self-service infrastructure.
• Promote DevSecOps and shift-left practices.

6. Quality Engineering

• Establish scalable automated testing strategy:
• Functional, integration, and contract testing
• End-to-end testing for user journeys
• Drive experimentation frameworks (A/B testing) for consumer features.
• Ensure observability into user experience metrics (latency, errors, drop-offs).

7. Performance Resiliency Engineering

• Design systems for peak traffic events and burst scalability.
• Implement:
• CDN strategies and caching layers
• Rate limiting and traffic shaping
• Lead performance benchmarking and tuning.
• Embed resilience patterns:
• Circuit breakers, retries, backpressure
• Chaos engineering and failure simulations
• Maintain high SLA/SLO for consumer-facing systems.

8. Stakeholder Management Product Alignment

• Partner with:
• Product management
• UX/design teams
• Data science analytics
• Translate business goals into consumer-centric technical solutions.
• Influence roadmap with data-driven insights and technical strategy.
• Communicate architecture and trade-offs to executive stakeholders.

9. Innovation Consumer Focus

• Drive innovation in:
• AI-first consumer experiences
• Hyper-personalization
• Real-time engagement
• Stay ahead of trends in consumer tech, including:
• Generative AI
• Mobile-first and omnichannel platforms
• Lead POCs and experimentation pipelines.