Senior Backend Engineer, Level AI
AI Agents
Human-quality AI for every customer interaction
Open for applications
Human-quality AI for every customer interaction
201-500 employees
Open for applications
201-500 employees
Company mission
To blend human and machine intelligence to transform customer experiences.
Role
Who you are
- 5+ years of experience in backend engineering, distributed systems, or platform engineering
- Strong experience building high-scale, production-grade backend systems
- Experience designing systems for real-time processing, streaming, or event-driven architectures
- Strong understanding of API design (REST, gRPC) and microservices architectures
- Experience with databases (SQL + NoSQL) and data modeling for high-scale systems
- Hands-on experience with Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure)
- Strong fundamentals in system design, concurrency, and performance optimization
Desirable
- Experience working with LLMs, conversational AI, or AI-powered products in production
- Familiarity with agent frameworks, tool calling, or multi-step reasoning systems
- Experience building or integrating RAG pipelines, vector databases, or retrieval systems
- Exposure to evaluation systems (offline/online evals, A/B testing for AI systems)
- Understanding of prompting strategies, context windows, and model behavior optimization
- Experience with real-time decisioning systems or workflow orchestration engines
What the job involves
- As a Senior Engineer – AI Agents, you will play a critical role in building the scalable backend systems that power Level AI’s next-generation AI Agents. These systems operate in real-time, high-volume enterprise environments and are central to delivering intelligent, production-grade AI experiences
- You will work at the intersection of distributed systems, cloud infrastructure, and AI-powered applications—bringing agentic AI capabilities into production at scale
- Design and build scalable backend systems powering AI Agents that operate in real-time enterprise environments
- Develop agent orchestration frameworks (multi-step reasoning, tool usage, decisioning workflows)
- Build systems for agent memory, context management, and state persistence across interactions
- Architect low-latency inference pipelines integrating LLMs, SLMs, and external tools/services
- Implement evaluation (evals) frameworks to measure agent performance, accuracy, and reliability
- Enable continuous improvement loops (feedback → retraining → deployment) for AI agents in production
- Design and manage event-driven, asynchronous workflows for complex agent tasks
- Optimize systems for high throughput, low latency, and cost-efficient inference at scale
- Build and maintain robust APIs and service layers (REST / gRPC) for agent capabilities
- Partner closely with Applied AI / ML teams to productionize models and agent behaviours
- Collaborate with Product and Solutions teams to translate real customer workflows into agentic systems
- Drive best practices in observability, monitoring, safety, and guardrails for AI systems
- Contribute to architecture decisions for scaling multi-tenant, enterprise-grade AI platforms
Our take
Contact centres play a critical role in modern businesses, yet they continue to face persistent challenges such as high staff turnover, operational inefficiencies, and the pressure of managing large volumes of customer interactions. On top of this, traditional approaches often struggle to consistently improve service quality while also ensuring customer data is handled securely.
Level AI addresses these issues with AI-powered tools designed to enhance contact centre operations, By leveraging generative AI and large language models (LLMs), the platform analyses customer conversations, delivers real-time support to agents, and automates processes such as quality assurance and sentiment analysis.
Following a significant funding round in 2024, the company announced plans to expand its team and accelerate product innovations. With this foundation, Level AIremains focused on helping organizations strengthen customer interactions and drive greater efficiency across their contact centre operations.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 4 rounds)
Jul 2024
$39.4m
SERIES C
Mar 2022
$20m
EARLY VC
Total funding: $74.4m
Company HQ
Old Mountain View, Mountain View, CA
Leadership
Ashish Nagar
(Founder & CEO)Previously a Product Manager at Amazon Alexa's Conversational AI Team. Worked as Director of Product & Business at both Relcy, Inc. and Kinestral Technologies Inc. Also worked as a Venture Capitalist at Investor Growth Capital and was a Senior Associate at The Boston Consulting Group.
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