Agentic AI Cloud Development Engineer

Description

This is a hybrid role: you will work on average 2 days per week from a company office.

The company is an edge-to-cloud business that helps customers connect, secure, analyze and act on their data and applications, from edge sites to the cloud.

You will join the team that builds the agentic workflows behind the company's AI assistant for network operations, which diagnoses, troubleshoots and resolves complex network problems on its own.

The work sits where data science, generative AI and production engineering meet: you will design, build and assess reasoning pipelines, tool-calling patterns, skills and MCP server integrations.

The ideal candidate has hands-on experience with LLM agent frameworks and the engineering discipline to ship reliable, observable AI systems in a cloud-native setting.

This is a subject matter expert role in agentic AI and applied GenAI. You will advise functional and technical teams, use significant independent judgment to reach goals, may join cross-functional initiatives, and may lead projects and mentor colleagues.

Job level: TCP02, within Engineering.

Responsibilities

• Build and iterate on agentic workflows in LangGraph.
• Create and maintain MCP (Model Context Protocol) servers and their skills: define tool schemas, build domain tools, write SKILL.md playbooks, and handle versioning, deployment and monitoring.
• Design and build streaming or batch applications on Kafka and Spark.
• Make LLM features hold up at production scale: structured outputs, streaming, function calling, prompt engineering, and error handling across every agent execution path.
• Work with network engineers and product managers to turn troubleshooting playbooks into agentic workflows, with the skills, tools and data pipelines they need.
• Write data analysis and transformation code that runs in sandboxed Code Mode environments, including scripts that orchestrate several tools, aggregate data and visualize results.
• Deploy and run containerized services on Kubernetes, improving CI/CD pipelines, container images, health probes and resource use.
• Own observability for agent workflows: tracing, logging, cost tracking and performance monitoring, so non-deterministic systems stay reliable in production.

Requirements

• Bachelor's or Master's degree in computer science.
• Usually 2 to 4 years building production ML or AI systems, including at least one year of hands-on work with generative AI and LLM applications.
• Skilled Python developer who writes production code, not only notebooks.
• Backend service development with FastAPI or equivalent, and REST or GraphQL API design.
• At least 2 years of relevant experience with big data tools such as Apache Spark and Kafka.
• Experience with agent orchestration frameworks such as LangGraph (strongly preferred), LangChain, Claude Agent SDK or equivalent, beyond prototypes.
• Hands-on work with MCP or similar tool-serving protocols: tool schema design, server implementation and registry management.
• Kubernetes experience: deploying, scaling and managing workloads, including Deployments, Services, ConfigMaps, Secrets and health probes.
• CI/CD pipeline experience for automated build, test and deploy, using Jenkins, GitHub Actions, ArgoCD or similar.
• Container image work: building, tagging and versioning with Docker, and familiarity with a registry such as ECR or GCR.
• Observability experience for AI systems with tools such as LangFuse, Prometheus or equivalent.
• Preferred: networking knowledge such as wireless or wired diagnostics and network troubleshooting, though not required.
• Preferred: experience with AWS Bedrock, OpenSearch Serverless or similar managed AI/ML services.
• Preferred: strong written and verbal communication, including explaining technical designs to senior leadership.

Conditions

Hybrid: on average 2 days per week in a company office.

Level TCP02 within Engineering.

Listed location: Puerto Rico.

The company is an equal opportunity employer that considers candidates regardless of race, gender or other protected category.

Benefits

• Comprehensive health and wellbeing benefits covering physical, financial and emotional health for employees and their families.
• Career development programs for goals such as becoming a recognised expert in your field or moving into another division.