Lead Engineer- Data Platforms, Performance & Agentic AI

Ideal Candidate Profile

Seeking a Lead Engineer- Data Platforms, Performance & Agentic AI that owns the technical architecture - full stack, strong data and app performance experience, Agentic AI with solid communication skills. Candidate should be skilled in designing and deploying agentic AI systems using LLMs and AI-assisted development tools. A strong technical leader with excellent communication skills, driving architecture, scalability, and engineering excellence and hands-on experience with Node.js, Python, React, and AWS, with proven experience in real-time data pipelines and event-driven architectures.

Job Duties & Responsibilities

• End-to-End Solution Ownership & Product Engineering (40%): Own delivery of complex, end-to-end engineering solutions—from data generation and ingestion through analytics, APIs, and user-facing experiences.
• Architecture, Data Engineering & Implementation (40%): Lead design and implementation of scalable, high-performance, cloud-native data and application platforms.
• Agentic AI & AI-Driven Development (20%): Design and build agentic AI systems that can autonomously reason, plan, and execute tasks across engineering workflows.

Required Skills & Experience

• 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.
• Strong experience designing and operating data pipelines and data platforms (real-time and batch).
• Experience building modern front-end applications (React/TypeScript) for data-intensive interfaces.
• Deep knowledge of AWS services (Lambda, S3, Step Functions, SNS/SQS, Redshift, Athena, DynamoDB, etc.).
• Experience with Infrastructure as Code (CDK, Terraform, CloudFormation).
• Strong understanding of event-driven architectures, streaming, and telemetry systems.
• Experience implementing observability and monitoring solutions (e.g., Grafana or similar).
• Experience with AI/ML systems in production, including model integration and operationalization.
• AI & Modern Engineering Capabilities: Experience working with LLMs, agent frameworks, or AI orchestration tools.

Preferred Skills

• Experience in high-scale, mission-critical environments with strict reliability requirements.
• Familiarity with cell-based or multi-tenant architectures.
• Experience designing systems for data isolation, security, and performance segmentation.
• Experience with synthetic data generation or simulation systems.
• Experience with multi-agent AI systems or advanced automation pipelines.