Lead Engineer – Data Platforms, Performance & Agentic AI (W2 Role)

Position: Lead Engineer (Contract) – Data Platforms, Performance & Agentic AI

Location: Remote (EST)

Duration: Multi-Year Contract

In this role, you will:

Architecture, Data Engineering & Implementation

• Lead 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
• Engineer high-performance systems, focusing on latency, throughput, resiliency, and cost efficiency
• Implement robust observability, telemetry, and performance monitoring across all layers
• Establish and enforce standards for automation, reliability, and performance engineering
• Integrate AI-driven components (prediction, anomaly detection, intelligent insights) into production systems

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

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

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

AI & Modern Engineering Capabilities

• 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