Senior Backend Engineer – AI & Data Systems

Team Red Dog • Redmond, WA

2d • Remote

About The Position

Team Red Dog is hiring a Senior Backend Engineer for a client described as a Fortune 50 technology leader and AI-driven organization. The role focuses on building scalable backend systems, synthetic data-generation workflows, and cloud-based data pipelines that support AI-powered enterprise experiences and Microsoft 365 Copilot innovation. The engineer will work across software engineering, large language models (LLMs), and data infrastructure, developing systems for data processing, orchestration, storage, and automated quality validation.

The position offers technical ownership and the opportunity to support AI prototyping, synthetic data generation, model evaluation, and product experimentation. The engineer will collaborate with engineers, designers, researchers, strategists, and product partners to develop practical technical solutions, evaluate architectural trade-offs, and improve enterprise AI experiences. The position is remote in the United States, with availability required for a portion of Pacific Time business hours. The schedule is Monday through Friday, 40 hours per week, with no overtime. This is a W2 contract opportunity through June 30, 2027, with potential extension up to 18 months total, subject to performance, budget, and client discretion. The rate is $81–$85 per hour. The estimated start date is immediately.

Qualified employees are offered a benefits package that includes health insurance (medical, dental, vision, and life), an employer-matched 401(k), paid time off, and a flexible paid holiday benefit. Applicants must be authorized to work in the United States without sponsorship. Employment is contingent upon successful completion of a reference and background check.

Requirements

• At least 5 years of professional software engineering, backend development, or data engineering experience building and supporting production systems.
• Strong programming skills in Python, Java/Spring Boot, .NET, or comparable backend languages and frameworks.
• Experience designing maintainable backend services, APIs, modular software components, and automated testing frameworks.
• Hands-on experience with data generation, ETL processes, distributed data processing, and scalable cloud-based pipelines.
• Strong understanding of LLM capabilities, limitations, prompting, evaluation methodologies, and AI workflow integration.
• Experience with workflow orchestration, asynchronous processing, concurrency, streaming or event-driven architectures, and failure recovery.
• Knowledge of large-scale data modeling, storage, partitioning, indexing, retrieval optimization, and database architecture.
• Strong analytical and troubleshooting skills, including quantitative performance measurement, data validation, and root-cause analysis.
• Practical cloud engineering experience deploying, monitoring, and operationally supporting production systems.
• Ability to work independently in established codebases, assess existing implementations, and deliver maintainable improvements.
• Strong communication, documentation, collaboration, and problem-solving skills, particularly in cross-functional engineering environments.
• Must be authorized to work in the United States without sponsorship.
• Employment is contingent upon successful completion of a reference and background check.

Nice To Haves

• Experience with Apache Spark, Kafka, or equivalent distributed processing and event-driven technologies.
• Familiarity with relational databases, NoSQL systems, cloud object storage, and data lake architectures.
• Experience integrating LLMs through AI platforms, frameworks, or APIs and evaluating production-oriented AI workflows.
• Experience with observability, performance tuning, and deployment automation.
• Previous Microsoft experience.

Responsibilities

• Design, develop, and enhance scalable synthetic data-generation systems that transform structured inputs, persona information, and organizational context into coherent, traceable, and reproducible datasets.
• Build and maintain cloud-based data pipelines, ETL workflows, and distributed processing systems for large-scale data generation and analysis.
• Develop orchestration workflows using concurrency, asynchronous execution, and robust error handling to improve pipeline reliability and scalability.
• Design and optimize data models, storage architectures, indexing strategies, and retrieval patterns for large datasets.
• Build automated validation frameworks and data-quality checks to measure accuracy, consistency, reproducibility, and system performance.
• Use quantitative analysis, profiling, and troubleshooting to identify bottlenecks, investigate system behavior, and improve operational efficiency.
• Develop, deploy, monitor, and support reliable backend services using cloud engineering and software development practices.
• Evaluate architectural approaches and technical trade-offs involving performance, scalability, maintainability, and cost.
• Collaborate with engineers, researchers, designers, and product stakeholders to turn evolving requirements into technical solutions.
• Maintain automated tests, technical documentation, and operational guidance to support system reliability and maintainability.

Benefits

• Health insurance, including medical, dental, vision, and life insurance.
• Employer-matched 401(k) plan.
• Paid time off.
• Flexible paid holiday benefit.

What This Job Offers

• Career Level: Senior
• Education Level: No Education Listed