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Sr. Software Engineer (Agentic Runtime)

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Dialpad

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Location:
Argentina , Buenos Aires

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

Dialpad’s AI Engineering organization is responsible for building and maintaining customer-facing AI features at scale across all of our cloud-native products and services. Dialpad's Agentic Runtime team owns the infrastructure and execution engine that runs AI agents at scale across Dialpad's core product modalities — including voice, messaging, video, and digital engagement.

Job Responsibility:

  • Contribute to the design, development, and maintenance of agentic runtime systems, including agent orchestration, tool execution pipelines, and multi-step reasoning loops
  • Build and optimize core runtime components, including task planners, action dispatchers, memory managers, and context window management systems
  • Work on agent coordination techniques, including dynamic tool selection, parallel agent execution, state management, and result aggregation across multi-agent workflows
  • Maintain and enhance highly scalable agentic platforms with a focus on low-latency execution, cost efficiency, and deterministic behavior
  • Ensure high availability, reliability, and fault tolerance in agent runtime services, including graceful degradation when LLM or tool calls fail
  • Collaborate with cross-functional teams — including ML researchers, product, and platform engineers — to translate agentic product requirements into robust runtime infrastructure
  • Develop and optimize real-time distributed systems, microservices, and event-driven architectures powering agentic task execution
  • Design and implement sandboxed execution environments for safe agent use of tools, code execution, and external API calls
  • Implement and maintain monitoring, alerting, and performance metrics covering agent run success rates, token consumption, latency, and cost attribution
  • Evaluate and integrate emerging agentic frameworks, LLM APIs, and tooling ecosystems to continuously improve platform capabilities
  • Write clean, modular, and well-tested code while following best engineering practices in a rapidly evolving problem space
  • Participate in code reviews to ensure the quality, maintainability, and scalability of runtime components
  • Provide mentorship and technical guidance to junior engineers navigating the unique challenges of agentic systems

Requirements:

  • 3–6 years of experience in distributed systems, platform engineering, or ML infrastructure, with exposure to LLM-based or agentic systems strongly preferred
  • Strong understanding of agent architectures, including ReAct, plan-and-execute, and multi-agent coordination patterns
  • Deep knowledge of context management, prompt lifecycle, tool-call protocols (e.g., function calling, MCP), and agent memory strategies (short-term, episodic, and long-term)
  • Experience integrating and managing external tool ecosystems, including web search, code interpreters, databases, and third-party APIs
  • Familiarity with retrieval-augmented generation (RAG) and how retrieval fits into broader agentic pipelines
  • Understanding of LLM output reliability challenges — hallucination, non-determinism, and retry/fallback strategies at runtime
  • Proficiency in Go and Python 3 (experience with Rust or TypeScript is a plus)
  • Strong understanding of distributed systems, microservices, and event-driven architectures suited to long-running agent tasks
  • Passion for real-time performance optimization, including streaming responses, async execution, and parallel tool invocation
  • Experience with API design using OpenAPI, Swagger, or equivalent, with an eye toward agentic interaction patterns
  • Knowledge of gRPC or equivalent RPC protocols for inter-service communication within agent runtimes
  • Experience with Docker and Kubernetes, including managing long-running or stateful agent workloads in containerized environments
  • Familiarity with cloud platforms (GCP preferred, AWS/Azure optional), including managed services relevant to agentic workloads such as queuing, secrets management, and compute autoscaling
  • Hands-on experience with Infrastructure as Code tools like Terraform or Ansible
  • Knowledge of CI/CD frameworks and continuous delivery practices, with comfort shipping infrastructure in a fast-moving research-adjacent environment
What we offer:
  • Competitive benefits and perks
  • Robust training program
  • Inclusive office environment
  • Recognized Great Place to Work culture

Additional Information:

Job Posted:
March 20, 2026

Work Type:
On-site work
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