AI Engineer

Seeking a hands-on AI Native Software Engineer to design, build, and deploy production-grade AI-driven systems within enterprise environments. The role focuseson implementing agent-based workflows, integrating AI platforms, and delivering scalable cloud-native solutions.

Required Skills & Experience

• Must be able and willing to travel 80-90% of the time to various customer sites
• Must be authorized to work in the U.S. without requiring sponsorship
• 8–10+ years of software engineering experience
• Strong experience with cloud-native systems (APIs, microservices, containers, serverless)
• Experience building and deploying AI/LLM-based systems in production (agents, RAG, orchestration)
• Proficiency in Python, Java, or similar backend languages

Experience with:

• CI/CD pipelines
• Infrastructure as code
• Monitoring and observability tools
• Hands-on experience with AI platforms (OpenAI, Claude, Vertex AI, or similar)

Preferred Experience

• Experience with agent frameworks (e.g., LangGraph, AutoGen, CrewAI)
• Experience designing multi-agent or distributed AI systems
• Familiarity with enterprise-scale system integration
• Experience optimizing AI workloads for cost and performance

Responsibilities

• AI Agent Engineering
• Design and implement AI agents, including:
• Retrieval (RAG)
• Orchestration workflows
• Tool/function invocation
• Policy-based routing
• Build evaluation frameworks for accuracy, latency, and reliability
• Implement observability and monitoring for agent lifecycle
• AI Platform Integration
• Integrate with AI providers (e.g., OpenAI, Anthropic, Google Vertex, open-source models)
• Build abstraction layers to support multi-model and multi-provider architectures
• Optimize model usage for performance, cost, and latency
• Cloud-Native Development

Develop scalable services using:

• Microservices architecture
• Containers (Docker, Kubernetes)
• Serverless and event-driven patterns
• Implement CI/CD pipelines and infrastructure as code (e.g., Terraform, Helm)
• Ensure production readiness, logging, monitoring, and fault tolerance

Application Development

• Build and deploy AI-powered applications aligned to business workflows
• Integrate AI systems into existing enterprise platforms and APIs
• Develop backend services and APIs supporting agent workflows

Testing & Performance

• Define and execute test strategies for AI systems
• Measure system performance (latency, throughput, accuracy, cost)
• Debug and optimize production systems

Scope & Expectations

• 100% hands-on engineering role (no people management)
• Deliver production-quality code and deployments
• Work within existing architecture and engineering standards
• Collaborate with client and internal engineering teams as needed
• Participate in technical design discussions (implementation-focused)