Software Engineer

Intone Networks Inc.; Northern, New York (KY, NY); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Intone Networks Inc. is seeking a Senior Software Engineer for a 12-month contract based in Park Ave, New York. The role focuses on reliability of AI platforms, with Kubernetes-based PaaS, model-agnostic gateways, and observability.

You will design systems to withstand failures and drive incident response while enabling self-service tooling. The ideal candidate has 6+ years in software engineering, strong Python skills, and hands-on AWS experience.

Qualifications

• 6+ years of professional software engineering experience.
• Strong Python skills and production-grade backend services and APIs.
• Experience designing and operating distributed systems in public-cloud environments with failure modes.

Responsibilities

• Improve platform reliability by designing for failure and meeting SLOs.
• Build Kubernetes-based PaaS frameworks and AI gateways.
• Develop model-agnostic gateway capabilities with providers such as OpenAI and AWS Bedrock.
• Create observability systems for metrics, logs, traces, dashboards, and alerting.
• Develop networking solutions across public-cloud and on-prem environments.
• Provision and manage cloud infrastructure using Terraform.
• Keep platforms secure via dependency patching and upgrades.
• Create templates and workflows to improve developer productivity.
• Evaluate emerging AI technologies to adapt the platform.

Skills

Python

Distributed systems

AWS

Terraform

Backend APIs

SLOs & incident response

Observability

Education

BS in CS or related field

Tools

OpenTelemetry

Prometheus

Grafana

Datadog

Kubernetes

AWS EKS

Karpenter

Job description

We are seeking a Senior Software Engineer for a 12-month contract position based in Park Ave, New York. The Agent Platform team is looking for candidates with Vue.js and Python experience to focus on the reliability and resilience of mission‑critical AI platforms. You will design systems that withstand provider and dependency failures, establish observability and service‑level objectives, and keep the platform current as the AI ecosystem evolves. The team's scope includes Kubernetes‑based platform‑as‑a‑service frameworks, model‑agnostic AI/LLM gateways, hybrid networking, observability, and self‑service developer tooling.

Responsibilities

• Improve platform reliability and resilience by designing for failure, defining and meeting SLOs, leading incident response, and reducing operational toil.
• Design, build, and operate Kubernetes‑based PaaS frameworks, AI/LLM gateways, APIs, and self‑service tools for AI applications.
• Develop model‑agnostic gateway capabilities for providers such as OpenAI, Anthropic, Gemini, and AWS Bedrock, including routing, fallback, retries, rate limiting, and cost controls.
• Build observability systems covering metrics, logs, traces, dashboards, and alerting to detect and resolve issues before they affect clients.
• Develop networking solutions that connect applications across public‑cloud and on‑premises environments.
• Provision and manage cloud infrastructure using Terraform and modern software engineering practices.
• Keep platforms secure and current through dependency patching, runtime upgrades, migrations, and provider‑integration updates.
• Create frameworks, templates, and workflows that improve developer productivity and reduce operational overhead.
• Evaluate emerging AI technologies and adapt the platform to support new development patterns and use cases.

Qualifications

• Required
  • 6+ years of professional software engineering experience.
  • Strong Python skills and experience developing production‑grade backend services and APIs.
  • Experience designing and operating distributed systems in public‑cloud environments, with a strong understanding of failure modes and resilient design patterns.
  • Hands‑on AWS experience, including services such as EC2, S3, IAM, and container‑based workloads.
  • Experience with Infrastructure as Code, preferably Terraform.
  • Experience with production operations, including metrics, logging, tracing, alerting, SLOs, and incident response.
  • Strong knowledge of software architecture, databases, networking, cloud infrastructure, and modern application development.
  • A degree in computer science, engineering, or a related field, or equivalent practical experience.
• Preferred
  • Java experience.
  • Experience building or operating API gateways, LLM gateways, or similar proxy layers with routing, fallback, rate limiting, caching, and cost tracking.
  • Experience with OpenTelemetry, Prometheus, Grafana, Datadog, or similar observability tools.
  • Experience with Kubernetes and autoscaling technologies, preferably Amazon EKS and Karpenter.
  • Knowledge of AWS networking and security, including VPC, Direct Connect, IAM, and cloud security controls.
  • Experience with chaos engineering, load and failure testing, capacity planning, or disaster recovery.
  • Experience developing AI‑powered applications, agent‑based systems, model‑inference services, or AI serving platforms.
  • Familiarity with AI development tools such as Claude Code, Cursor, or GitHub Copilot.
  • Working knowledge of machine learning concepts and the ML development lifecycle. Experience with SageMaker, Bedrock, PyTorch, TensorFlow, or scikit‑learn is a plus.
  • The ability to learn quickly and independently lead large technical initiatives from concept through production.