DevOps Engineer

Position:

Location:

DevOps Engineer (Infrastructure Generalist)

At Incept Labs, we believe the future of education and research lies in humans and AI working

together side by side. AI brings the ability to process knowledge at scale, while people

contribute imagination, values, and lived experience. When combined, they create a partnership

where each strengthens the other, opening new ways to discover, adapt, and grow.

We are a small team of scientists, engineers, and builders who are passionate about building

domain-specific, next-generation AI solutions to enhance education and research.

About This Role

We're looking for an Engineer experienced in DevOps, preferably with experience filling in as an

infrastructure/backend engineering generalist.

We view infrastructure as a critical component, as it enables every breakthrough. You'll work

directly with researchers to accelerate experiments, optimize efficiency, and enable key insights

across our models and data assets.

You’ll join a high-impact, compact team responsible for both architecture and scaling of Incept’s

core infrastructure. Work will span the full technical stack and involve solving complex

distributed systems problems as well as building resilient, scalable platforms.

Responsibilities

• Design, build, and operate scalable, fault-tolerant infrastructure to support distributed computing and data orchestration for LLM Research
• Develop and maintain high-throughput systems for data ingestion, processing, and transformation to support LLM model development
• Collaborate with research teams to improve system efficiency and accelerate model training and evaluation cycles
• Implement and maintain monitoring and alerting to support platform reliability and performance
• Build systems for traceability, reproducibility, and robust quality control to ensure adherence to industry compliance standards

Required Qualifications

• 5+ years of experience building and maintaining distributed systems, ideally supporting high-scale applications or research platforms.
• Fluent in containerization, orchestration, and distributed computing frameworks.
• Extensive experience with performance optimization, caching strategies, and system scalability patterns.
• Knowledge of and experience with specialized hardware (GPUs, TPUs) computing and GPU cluster management
• Strong knowledge of databases, storage systems, and how architecture choices impact performance at scale.
• Deeply familiar with cloud infrastructure, microservices architectures, and both synchronous and asynchronous processing.
• Proactive about automation, testing, and building tools that empower engineering teams.

This role is fully remote, India-based. Compensation and benefits will vary based on

background, skills, and experience levels.