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Lingopal · 2 weeks ago

Backend Technical Lead

Chicago

Full-time

Onsite

Lead/Staff

10+ years exp

Lingopal.ai is a mission-driven company focused on redefining global communication through AI technology. They are seeking a Backend Technical Lead to design and implement core systems, mentor developers, and ensure infrastructure can handle high traffic for their live translation engine.

Artificial Intelligence (AI)BroadcastingMedia and EntertainmentSoftwareTranslation Service

Responsibilities

Architect & Build: Design, code, and deploy high-performance backend services using Python. You will own the architecture that orchestrates AI models, video ingestion, and real-time delivery

Technical Leadership: Lead a team of talented engineers. You will drive code reviews, set engineering standards, and mentor the team to foster technical growth

Scale for Growth: Transition our systems to a robust, globally distributed architecture capable of handling massive spikes in traffic

Infrastructure Ownership: With the support of our DevOps team, manage cloud infrastructure, ensuring high availability and fault tolerance

Optimize Performance: Identify bottlenecks in the translation pipeline and optimize for throughput and latency

Qualification

Python ExpertiseSystem DesignCloud InfrastructureTechnical LeadershipContainerizationAI/ML IntegrationVideo EngineeringOrchestrationAudio Signal ProcessingStartup DNAObservability

Required

10+ years of professional software development experience

B.S. in Computer Science or equivalent

Demonstrated ability to lead technical teams, drive consensus on architectural decisions, and mentor junior/mid-level engineers

Deep, production-level experience with Python and its concurrency models (asyncio, threading, multiprocessing)

Proven track record of designing and building scalable, distributed services in a cloud environment (AWS, GCP, or Azure)

Proficiency with Docker and container orchestration concepts

You thrive in fast-paced environments, possess a high sense of ownership, and are comfortable navigating ambiguity

Preferred

Experience with Rust for performance-critical components

Experience using and deploying ML models in production

Familiarity with GStreamer, FFmpeg, or WebRTC protocols

Professional experience with low-latency audio processing algorithms and/or a strong intuition for sound quality (e.g., being an audiophile or musician is a plus)

Hands-on experience with production Kubernetes clusters

Experience with monitoring and alerting stacks like Prometheus and Grafana