AI Native Software Engineer

Key Responsibilities

• Design and implement AI agents (RAG, orchestration workflows, tool/function invocation, policy-based routing).
• Build evaluation frameworks for accuracy, latency, and reliability; implement observability and monitoring.
• Integrate with AI providers (OpenAI, Anthropic, Google Vertex) and open-source models; create abstraction layers.
• Optimize model usage for performance, cost, and latency in production.
• Develop scalable services using microservices, containers (Docker, Kubernetes), serverless, and event-driven patterns.
• Implement CI/CD pipelines and infrastructure as code (Terraform, Helm); ensure logging and fault tolerance.
• Build and deploy AI-powered applications aligned to business workflows.
• Develop backend services and APIs supporting agent workflows and enterprise integration.
• Define test strategies for AI systems; measure latency, throughput, and cost; debug and optimize production systems.

Required Skills & Qualifications

• 8–10+ years of software engineering experience.
• Proficiency with cloud-native systems (APIs, microservices, containers, serverless).
• Experience building and deploying AI/LLM systems in production (agents, RAG, orchestration).
• Proficiency in Python, Java, or similar backend languages.
• Hands-on experience with CI/CD pipelines, infrastructure as code, and monitoring tools.
• Practical experience with AI platforms (OpenAI, Claude, Vertex AI, or similar).

Benefits

• Major medical, HSA, dental, vision
• Employer-provided group life and voluntary life insurance
• Short-term and long-term disability
• 401k