#Hybrid
DriveNets builds high-performance networking solutions for large-scale AI infrastructure and service-provider networks. DriveNets’ Network Cloud powers production networks at global operators such as AT&T and Comcast, while its AI Fabric solutions optimize the performance and time to first token (TTFT) in multi-vendor AI environments at foundation model labs, NeoClouds, and enterprises. DriveNets combines high-performance networking, end-to-end automation, and full-stack AI cluster optimization to remove network bottlenecks, maximize GPU utilization, accelerate AI cluster deployments, and improve token economics
Job Summary
We are looking for a talented and motivated Software Engineer with hands-on experience building and operating multi-agent AI systems in production to join our DriveNets Automation Platform (DAP) team.
The team develops automation tools, orchestration capabilities, and intelligent platforms that simplify the deployment, management, troubleshooting, and optimization of large-scale network and AI infrastructure environments.
You will work on the design and development of AI-powered systems that bridge networking, automation, observability, and distributed infrastructure — running on Kubernetes at scale. Our stack includes LangGraph, Langfuse, RAG pipelines, MCP, and agent-to-agent (A2A) communication patterns.
This role combines strong software engineering with practical AI application development, with a sharp focus on production hardening, tracing, evaluation, and safety of agentic systems — not model training or research prototypes.
Requirements- 8+ years of hands-on software engineering experience building production-grade backend services, APIs, or AI-powered systems.
- Proven production experience with multi-agent AI systems: deployment, tracing, guardrails, hardening, and incident management.
- Hands-on experience with agentic frameworks such as LangGraph, CrewAI, Google ADK, AutoGen, or equivalent.
- Experience building and running evaluation pipelines for agentic solutions - including trajectory tracing, ground truth validation, and harshness/quality scoring.
- Strong Python proficiency: comfortable building scalable backend services using gRPC and REST APIs.
- Solid understanding of distributed systems: fault tolerance, consistency models, service communication, and operational challenges at scale.
- Hands-on Kubernetes experience: deploying and operating containerized services, managing workloads, config, and scaling in production clusters.
- Practical experience with embeddings, vector databases, and semantic retrieval systems in production.
- Practical experience with RAG pipelines, LLM API integration, structured outputs, and tool calling in production environments including building and serving MCP servers at scale.
- Working knowledge of SQL and/or NoSQL databases, schema design, and query optimization.
- Strong debugging skills across application logic, APIs, data, and AI agent behavior.
- Strong communication skills and a bias toward ownership and delivery.
Nice to Have
- Familiarity with Langfuse/Arize Pheonix.
- Familarity with A2A & A2UI protocols.
- Experience with network automation, orchestration, or configuration management (Ansible, Terraform, NETCONF, gNMI, or similar).
DriveNets is on a mission to build a special company comprised of individuals with diverse backgrounds, perspectives, and experiences.
DriveNets is an equal opportunity employer. We do not discriminate based on upon race, religion, national origin, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with disability, or other applicable legally protected characteristics.
Skills Required
- 8+ years of hands-on software engineering experience building production-grade backend services, APIs, or AI-powered systems.
- Production experience with multi-agent AI systems, including deployment, tracing, guardrails, hardening, and incident management.
- Hands-on experience with agentic frameworks such as LangGraph, CrewAI, Google ADK, AutoGen, or equivalent.
- Experience building and operating evaluation pipelines for agentic solutions, including trajectory tracing, ground truth validation, and quality scoring.
- Strong Python proficiency and experience building scalable backend services with gRPC and REST APIs.
- Solid understanding of distributed systems, fault tolerance, consistency models, service communication, and operations at scale.
- Hands-on Kubernetes experience deploying and operating containerized services in production clusters.
- Production experience with embeddings, vector databases, and semantic retrieval systems.
- Experience with RAG pipelines, LLM API integration, structured outputs, tool calling, and MCP servers.
- Working knowledge of SQL and/or NoSQL databases, schema design, and query optimization.
- Strong debugging skills across application logic, APIs, data, and AI agent behavior.
- Strong communication skills and ownership mindset.
- Familiarity with Langfuse or Arize Phoenix.
- Familiarity with A2A and A2UI protocols.
- Experience with network automation, orchestration, or configuration management using Ansible, Terraform, NETCONF, gNMI, or similar tools.
What We Do
DriveNets is a rapidly growing software company that has created a radical new way for service providers and hyperscalers to build their networking infrastructure. DriveNets Network Cloud and DriveNets Network Cloud-AI are new innovative networking solutions that apply the cloud architectural approach to high-scale networking. They bring together the scalability of standard Ethernet Clos architecture with the high performance and reliability of service provider networking, delivering optimal networking performance, scale and cost structure for service providers and hyperscalers. Founded by Ido Susan and Hillel Kobrinsky, two successful telco entrepreneurs, DriveNets Network Cloud is the leading open disaggregated networking solution based on cloud-native software running over standard white boxes. Over three funding rounds, DriveNets raised $587 million. Its solutions are used by tens of service providers globally and are in proof-of-concept and lab trials at dozens of operators and hyperscalers, consistently ranking #1 in trials for breadth of capabilities and solution quality. AT&T, the largest backbone in the US, deployed DriveNets Network Cloud across its core network, and DriveNets is currently transporting more than 52% of AT&T’s core network traffic. DriveNets is engaged with over 100 Tier-1 operators and cloud-providers on large projects in North America, Asia and Europe.
