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AI Native Software Engineer (Please only apply if you are Local to Dallas)

1 point system3 months ago
Dallas, TX, United States
Remote
Full-time
Junior Level (1-3 years)
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Job Description

Key Note

Resume must include the product/application/system delivered into production

Must‑Have Requirements

  • Seniority: 8–10+ years software engineering experience; Senior/Lead IC; technical pod lead.
  • Enterprise Experience: Large enterprise systems, high‑visibility, multi‑user environments.
  • Production AI:
  • Built & supported AI systems in production (not POCs/demos).
  • Hands‑on with agents, RAG, orchestration workflows.
  • Monitoring, logging, performance, latency, reliability, debugging.
  • Engineering Depth: Personally writes, deploys, debugs code; can explain build, tradeoffs, challenges.
  • Cloud Native & Tooling:
  • APIs/microservices
  • Containers (Docker/Kubernetes) or serverless
  • CI/CD pipelines
  • Infrastructure as Code (Terraform, Helm)
  • Monitoring/observability tools
  • Resume/LinkedIn Quality: Clean, concise, error‑free; consistent dates/titles; clear ownership & outcomes.

Responsibilities

  • AI Agent Engineering: Retrieval (RAG), orchestration workflows, tool/function invocation, policy‑based routing.
  • Evaluation & Monitoring: Accuracy, latency, reliability frameworks; observability for agent lifecycle.
  • AI Platform Integration: OpenAI, Anthropic, Vertex AI, OSS models; abstraction layers; cost/performance optimization.
  • Cloud‑Native Development: Microservices, containers, serverless, CI/CD, IaC, monitoring, fault tolerance.
  • Application Development: AI‑powered apps, enterprise platform/API integration, backend services for agent workflows.
  • Testing & Performance: Test strategies, latency/throughput/accuracy/cost measurement, debugging production systems.

Required Skills

  • Python, Java, or similar backend languages.
  • Cloud‑native systems (APIs, microservices, containers, serverless).
  • CI/CD pipelines, Infrastructure as Code, monitoring/observability.
  • Hands‑on with AI platforms (OpenAI, Claude, Vertex AI, etc.).

⭐ Preferred Skills

  • Agent frameworks (LangGraph, AutoGen, CrewAI).
  • Multi‑agent/distributed AI systems.
  • Enterprise‑scale system integration.
  • AI workload optimization (cost/performance).

Required Skills

Monitoring and observability tools
AI platforms (OpenAI, Vertex AI)
Microservices architecture
Java
Python
CI/CD pipelines
Containerization (Docker, Kubernetes)
Infrastructure as Code (Terraform, Helm)