AI Agent Engineer

Overview

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

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.

Required Skills & Experience

• 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.

• 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)