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Teja Potineni is an accomplished Senior Software Engineer with approximately 9 years of experience in designing, developing, and deploying scalable and resilient software systems. With a strong foundation in backend technologies, cloud platforms, and distributed architectures, Teja has a proven track record of delivering high-impact solutions in fast-paced tech environments. He is passionate about tackling complex technical challenges, mentoring team members, and driving innovation in software engineering practices. His expertise often lies in areas such as microservices, API design, and data-intensive applications.
Teja Potineni's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Successfully led a cross-functional team to re-architect and implement a critical backend service, resulting in a 30% improvement in system performance and a 20% reduction in operational costs.
Played a key role in migrating legacy on-premise applications to a modern cloud infrastructure (e.g., AWS or GCP), enhancing scalability and reliability while optimizing resource utilization.
Recognized for outstanding contributions to a flagship product, demonstrating exceptional problem-solving skills and technical leadership in delivering a complex feature ahead of schedule.
Designed and implemented an automated testing and deployment pipeline that significantly reduced manual effort and improved the release cycle time for new software versions.
Northeastern University - Year 2002
Highperformr Signals uncover buying intent and give you clear insights to target the right people at the right time — helping your sales, marketing, and GTM teams close more deals, faster.
Vassar Labs is an Agri-Tech company specializing in IoT (Internet of Things) and AI-based solutions for data-driven farming. They aim to empower farmers and agricultural stakeholders with actionable insights derived from real-time data analytics. Their offerings typically include solutions for irrigation automation, crop health monitoring, pest and disease prediction, soil moisture sensing, and yield estimation, ultimately contributing to improved crop yields, resource optimization (like water and fertilizers), and sustainable agricultural practices.
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