Sr. AI Engineer

Sr. AI Engineer

Hybrid (Atlanta, Austin, Boston, Charlotte, Chicago, Cinccinati,Cleveland, Columbus, Dallas, Denver,Detroit, Hartford,Houston,Indianapolis, Irvine,Kansas City, LA, Miami, Milwaukee,Minneapolis, New York,Philadlphia, Pheonix, Pittsburg,Raleigh,San Antonio,Seattle,St. Louis,Tampa, Washington DC )

Long Term

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

• 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 multiple 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 (Contractor-Specific)

• 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)