Lead Engineer,Full Stack Platform Engineer Job Reston area,Virginia USA,Software Development

Lead Engineer, Full Stack Platform Engineer

Location:

Remote EST Duration:
Long Term Contract Team:
The team owns the platform end-to-end—from data generation and ingestion through application delivery and user experience. We are responsible for building and maintaining high-performance, resilient systems, with a strong emphasis on performance engineering, scalability, and operational readiness. A key part of our mission is enabling the organization through robust test data generation and simulation capabilities that support platform validation, reliability testing, and AI model development.

Must

Have

Skills:

Agentic AI
AWS Dynamo
AWS Elastic Search
AWS Event Bridge
AWS Kinesis
AWS Lambda
AWS Open Search
AWS S3
AWS SNS/SQS
JavaScript ES6
Node

Profile:
Lead Engineer that owns the technical architecture - full stack, strong data and app performance experience, Agentic AI solid communication skills

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
Develop a deep understanding of business workflows, especially high-scale exam and operational systems
Partner with product, architecture, and engineering teams to shape requirements, define scope, and provide accurate level-of-effort estimates
Drive sprint planning, technical design discussions, and code/design reviews with a focus on speed, quality, and scalability

Architecture, Data Engineering & Implementation (40%)

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 (20%)

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:

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 (Type Script 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/Type Script) 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, Cloud Formation)
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., Git Hub Copilot, ChatGPT, or similar) and integrating them into development workflows
Understanding of RAG architectures, prompt engineering, and…