Top Tech Jobs & Startup Jobs

Lead Kubernetes and GPU-focused infrastructure: drive FinOps and right‑sizing, optimize on‑prem GPU throughput, build tooling and dashboards for backend teams, ensure reliability instrumentation, and own selected platform security workstreams.

Seeking a QA Engineer to develop automation tests, collaborate cross-functionally, and enhance product quality at Level AI, focusing on AI-driven testing and performance validation.

Build and own end-to-end full-stack features for real-time AI-assisted agent workflows. Implement React front-ends, Django/NestJS backends, scalable APIs, integrations with cloud and event-driven pipelines, and reusable components for customer-facing enterprise products.

As an AI Analyst, you'll drive product impact through quantitative research, conduct data analysis, optimize AI model performance, and generate business analysis reports.

Hire, train, and scale an SDR team to generate pipeline through outbound and inbound prospecting. Set KPIs, design sequences, run coaching and reviews, analyze performance, partner with marketing, own playbook and tooling, and develop SDR-to-AE career paths.

As a Senior Backend Engineer, you will design and maintain scalable software solutions, embrace innovation with AI tools, and ensure high-quality engineering practices.

Lead end-to-end implementation of AI virtual agents and CX automation: scope, configure workflows, build integrations, validate performance and guardrails, and partner with customers and product/engineering to optimize deployments.

The Lead Software Engineer - AI Agents will design scalable backend systems for AI Agents, developing frameworks for multi-step reasoning and context management, optimizing for performance and cost-efficiency while collaborating with teams to implement best practices for observability and safety in AI systems.

As a Machine Learning Engineer at Level AI, you'll work on NLP challenges, develop scalable solutions, collaborate with teams, and innovate using cutting-edge ML techniques.

Design, build, and maintain backend systems for an AI-driven contact center platform. Implement REST APIs, database schemas, ETL pipelines, caching, and background jobs; deploy and operate services on GCP using Kubernetes and CI/CD. Collaborate on architecture, ensure engineering best practices, and deliver production-grade features.