Lead Engineer, Full Stack Platform Engineer

Technical Leadership & Engineering Excellence

Act as a senior technical leader driving architectural decisions and solving complex system challenges.

Mentor engineers across backend, data, performance, and AI domains.

Champion engineering best practices in performance optimization, scalability, security, and reliability.

Clearly communicate technical strategy, tradeoffs, and decisions to stakeholders.

Agentic AI & AI-Driven Development

Design and build agentic AI systems that can autonomously reason, plan, and execute tasks across engineering workflows.

Leverage LLMs and orchestration frameworks to enable intelligent automation in data pipelines, testing, and operations.

Incorporate AI-assisted development practices, including code generation, code review augmentation, and developer productivity tooling.

Evaluate and implement AI-native architectures, including tool-using agents, multi-agent systems.

Ensure responsible, secure, and scalable deployment of AI capabilities in production environments.

Performance Engineering & Operational Readiness

Lead performance engineering efforts, including load testing, capacity planning, and system tuning.

Build frameworks for data-driven performance benchmarking and optimization.

Ensure systems meet strict SLAs for availability, latency, and scalability.

Proactively identify risks and ensure readiness for high-stakes operational events.

About You

You have:

• 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.
• Experience working with LLMs, agent frameworks, or AI orchestration tools.
• Familiarity with agentic workflows, autonomous system.
• Hands-on experience with AI-assisted coding tools (e.g., GitHub Copilot, ChatGPT, or similar) and integrating them into development workflows.
• Understanding of RAG architectures, prompt engineering, and tool-augmented AI systems.

Nice to Have

• 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.
• Exposure to synthetic data generation or simulation systems.
• Experience with multi-agent AI systems or advanced automation pipelines.
• Experience with MCP servers and agents skills.