Technical Lead, Data Systems & Infrastructure

As a Technical Lead for Data Systems & Infrastructure at Lightfield, your primary responsibilities will include architecting and scaling the data infrastructure, optimizing search and retrieval systems that drive our AI-powered CRM. You will design data models to enhance CRM workflows and develop systems to ensure reliability and performance while mentoring teammates and contributing to the engineering culture.

To qualify for the Technical Lead position at Lightfield, candidates should have over 10 years of experience in development, specializing in infrastructure and data modeling. Familiarity with database design, particularly PostgreSQL, as well as experience with full-text search infrastructure like Typesense, is essential. Proficiency in building scalable data systems is crucial, along with a strong understanding of software engineering principles.

A Technical Lead at Lightfield should have a strong foundation in technologies such as TypeScript, React, Next.js, Node.js, and Apollo GraphQL. Additionally, experience with PostgreSQL, Typesense, and Pinecone for vector and semantic search will be vital. Familiarity with graph databases like Neo4j is a plus, enhancing your ability to model complex relationships.

Lightfield's CRM stands out due to its collaborative design tailored to help founders engage with customers effectively. The Technical Lead contributes by developing robust data infrastructures that allow for rapid insights and automation, enhancing the overall user experience and ensuring that the CRM is not only fast and intuitive but also indispensable.

The team culture at Lightfield is defined by collaboration, mentorship, and knowledge-sharing. As a Technical Lead, you will play a vital role in shaping this environment, participating in code reviews, mentoring peers, and promoting best engineering practices within a fast-paced and dynamic team.

When designing a scalable data infrastructure, it's essential to assess the specific needs of the application. Start by outlining data flow requirements, understanding user interactions, and anticipating future scaling challenges. Use modular design principles to ensure that components can be independently scaled and optimized, while also focusing on performance metrics to guide your architecture decisions.

I have extensive experience in creating sophisticated data models that align with use cases. For indexing strategies, I prioritize optimizing the read and write performance by using the right indexing techniques. Crafting indexes tailored to user queries can greatly enhance retrieval times, and I always consider balancing speed against storage efficiency.

One notable full-stack system I worked on involved creating a comprehensive e-commerce platform. The architecture was designed with microservices for the backend using Node.js and Express, and the front end was built with React. This modular approach allowed for independent scaling of services and smooth user experiences, ensuring reliability and performance throughout.

To ensure observability, I implement logging and monitoring solutions that provide real-time insights into system performance. Using tools like Prometheus and Grafana, I set up dashboards to track key metrics and alerts for anomalies. This proactive approach enables quick detection of issues, allowing for timely interventions before they escalate.

I have worked on numerous AI-driven projects that utilized both traditional relational databases and modern solutions like vector databases. My experience includes integrating machine learning models with data storage, facilitating contextual search tasks. Leveraging tools that support semantic search like Pinecone has enhanced our model's ability to deliver personalized insights.

When faced with ambiguity, I proactively engage stakeholders to clarify key outcomes and expectations. I find that maintaining open lines of communication and iteratively refining project goals can transform vagueness into actionable tasks. This approach helps in fostering alignment and ensuring the final product meets user needs effectively.

To optimize search capabilities, I implement various techniques, including indexing strategies and query optimization. Utilizing full-text search tools, I define relevant search criteria to enhance result accuracy. Also, experimenting with caching strategies ensures frequently accessed data is delivered quickly while reducing the load on databases.

I believe in a collaborative mentoring style that encourages knowledge sharing and active participation. Rather than just providing answers, I guide team members through problem-solving processes, fostering critical thinking and independent learning. This approach not only boosts individual confidence but also strengthens the team's overall competence.

Staying updated with technology trends is vital in our field. I regularly attend industry conferences, participate in webinars, and engage in online forums. Additionally, I’m an avid reader of tech blogs and research papers, ensuring that my knowledge remains current and applicable.

I thrive in fast-paced environments as they constantly offer new challenges and learning opportunities. The chance to innovate and contribute to a groundbreaking product like Lightfield’s CRM motivates me greatly. The dynamic nature of the role allows for both creative thinking and practical problem-solving, ultimately resulting in a rewarding experience.