Lead Engineer

About the role

Own delivery of complex, end-to-end engineering solutions, from data generation and ingestion through analytics, APIs, and user-facing experiences. Lead the design and implementation of scalable, high-performance, cloud-native data and application platforms. Architect data generation systems (synthetic, event-based, telemetry-driven) to support testing, analytics, and AI model development. Integrate AI-driven components (prediction, anomaly detection, intelligent insights) into production systems. Design and build agentic AI systems that can autonomously reason, plan, and execute tasks across engineering workflows. Act as a senior technical leader, driving architectural decisions and solving complex system challenges.

Responsibilities

• Own delivery of complex, end-to-end engineering solutions, from data generation and ingestion through analytics, APIs, and user-facing experiences
• Lead the design and implementation of scalable, high-performance, cloud-native data and application platforms
• Architect data generation systems (synthetic, event-based, telemetry-driven) to support testing, analytics, and AI model development
• Integrate AI-driven components (prediction, anomaly detection, intelligent insights) into production systems
• Design and build agentic AI systems that can autonomously reason, plan, and execute tasks across engineering workflows
• Act as a senior technical leader, driving architectural decisions and solving complex system challenges

Requirements

• 7+ years of experience building and operating scalable, distributed, cloud-native systems, including data platforms and APIs
• Strong experience with end-to-end system design, from data generation to front-end delivery
• Proven expertise in performance engineering, including profiling, load testing, and system optimization
• Hands-on experience with backend technologies such as Node.js (TypeScript preferred) and Python, building APIs and event-driven systems
• Deep knowledge of AWS services (Lambda, S3, Step Functions, SNS/SQS, Redshift, Athena, DynamoDB, etc.)
• Experience working with LLMs, agent frameworks, or AI orchestration tools, and AI-assisted coding tools

Benefits

• Opportunity to drive significant technical impact within a critical platform team
• Exposure to cutting-edge AI technologies and agentic AI systems
• A culture that champions engineering best practices in performance optimization, scalability, security, and reliability
• Collaborative environment with a focus on mentorship and continuous learning