Title: Lead Engineer, Full Stack Platform Engineer
Location: Remote
Duration: Long Term Contract
Profile: Lead Engineer that owns the technical architecture - full stack, strong data and app performance experience, Agentic AI solid communication skills
In this role, you will:
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
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
What We re Looking For
- Strong ownership mindset with the ability to drive end-to-end delivery
- Deep focus on performance, scalability, and reliability
- Curiosity and hands-on engagement with emerging AI technologies
- Ability to operate effectively in a fast-moving, contract-based environment
- Clear communication and strong collaboration across technical and non-technical stakeholders
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