Lead Engineer� Data Platforms, Performance & Agentic AI

Accylerate, LLC.; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Accylerate, LLC. is seeking a Lead Engineer for Data Platforms, Performance & Agentic AI. You will own the technical architecture across full stack, with strong data and performance experience.

The role demands hands-on work with Node.js, Python, React, and AWS, plus real-time data pipelines and event-driven systems. You will lead design, implementation, and optimization of cloud-native platforms, scale data-generation systems, and integrate AI-driven components while ensuring observability,

Qualifications

• 7+ years of experience building and operating scalable, distributed, cloud-native systems.
• Strong experience with end-to-end system design from data generation to front-end delivery.
• Proven expertise in performance engineering, profiling, load testing, and optimization.
• Hands-on backend experience with Node.js/TypeScript and Python, building APIs and event-driven systems.
• Experience designing and operating data pipelines and data platforms (real-time and batch).
• Experience with modern front-end apps (React/TypeScript) for data-intensive interfaces.
• Deep knowledge of AWS services (Lambda, S3, Redshift, DynamoDB, etc.).
• Experience with Infrastructure as Code (CDK, Terraform, CloudFormation).
• Familiarity with AI/ML systems in production, including model integration.

Responsibilities

• Own delivery of complex, end-to-end engineering solutions from data generation through analytics, APIs, and user-facing experiences.
• Develop deep understanding of business workflows, especially high-scale exam and operational systems.
• Partner with product, architecture, and engineering teams to shape requirements and estimates.
• Drive sprint planning, technical design discussions, and code/design reviews with focus on speed and quality.
• Lead design and implementation of scalable, high-performance cloud-native data platforms.
• Architect data generation systems to support testing, analytics, and AI model development.
• Engineer high-performance systems focusing on latency, throughput, resiliency, and cost.

Skills

Node.js

Python

React

TypeScript

AWS

Data pipelines

Performance engineering

Event-driven architectures

LLMs

AI orchestration

Tools

AWS CDK

Terraform

CloudFormation

Grafana

Job description

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 solutionsfrom 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

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
• 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

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
• Exposure to synthetic data generation or simulation systems
• Experience with multi-agent AI systems or advanced automation pipelines