Software Engineer - AI Native Engineering

CEdge Inc
St. Louis, MO, United States
5 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Automation of Tests Cloud Engineering Continuous Integration Distributed Systems Amazon DynamoDB Identity and Access Management Software Engineering GitHub Copilot Retrieval-Augmented Generation
+10 more
System Availability Large Language Models Backend AI Platforms Kubernetes Low Latency Api Design Terraform Docker Microservices

Job description

We are seeking a battle-hardened Senior Software Engineer to lead the transition from traditional software development to AI-Native Engineering. This is a high-impact, production-focused role. This is not a research position, nor is it a playground for prototypes; you will be responsible for architecting, shipping, and maintaining the agentic workflows and developer enablement platforms that define our core engineering future.

The ideal candidate views LLMs as a fundamental compute primitive. You are someone who has moved beyond “prompting” and into building robust, autonomous systems. Your daily drivers include GitHub Copilot and Claude Code CLI, and you have a proven track record of shipping complex backend systems at scale on AWS.

Key Responsibilities

  • Architecting Agentic Systems: Design and deploy production-grade agentic workflows that orchestrate multi-step tasks, utilizing LLMs for reasoning and autonomous execution.

  • Modern Cloud-Native Backend: Build and scale distributed systems on AWS, ensuring high availability, performance, and security for all AI-integrated services.

  • AI-Assisted Velocity: Champion AI-native development workflows, maintaining an elite delivery pace through the expert use of AI coding assistants and mentoring the broader team on these methodologies.

  • Developer Enablement Platforms: Build internal tools and extend Model Context Protocol (MCP) servers to allow product teams to integrate AI capabilities seamlessly and safely.

  • LLM Observability & Governance: Implement comprehensive monitoring (latency, cost, token usage) and rigorous evaluation frameworks to mitigate hallucinations and ensure reliability.

  • Engineering Excellence: Maintain a rigorous standard for CI/CD, containerization (Docker/Kubernetes), and Infrastructure-as-Code (Terraform/CDK) in an AI-driven environment., A history of building internal developer productivity tools or custom CLI utilities.

What Success Looks Like in 6 Months

  • 30 Days: You have integrated into the Core Engineering team, established an elite development velocity using AI-native tools, and contributed to the existing AI platform codebase.

  • 90 Days: You have architected and shipped a production-ready agentic workflow that measurably improves developer productivity or automates a core operational bottleneck.

  • 180 Days: You have established a standardized framework for LLM observability and governance across the organization, enabling three or more product teams to deploy AI features with confidence.

Requirements

  • Senior Experience: 8+ years of professional software engineering experience in enterprise-grade production environments.

  • Active IC Coding: You must be a hands-on builder with significant code contributions in a production codebase within the last 6 months.

  • AI Tooling Mastery: Daily, expert-level use of GitHub Copilot, Claude Code CLI, or similar AI-assisted development tools.

  • Shipped AI Systems: You have personally architected and delivered at least one agentic or LLM-powered system to production that handled real-world traffic.

  • AWS Depth: Expert knowledge of the AWS ecosystem, specifically Bedrock, Lambda, ECS/EKS, DynamoDB, and IAM.

  • Software Fundamentals: Deep expertise in microservices, distributed systems architecture, API design (REST/gRPC), and automated testing.

Preferred Qualifications & Strong Signals

Category

Preferred Expertise & Tooling

Extensibility

Practical experience building or extending Model Context Protocol (MCP) servers.

Agent Frameworks

Hands-on experience with LangGraph, CrewAI, AutoGen, or AWS Bedrock Agents.

Enterprise APIs

Deep familiarity with production integration of Bedrock, Anthropic, and OpenAI APIs.

Advanced RAG

Experience with production-grade RAG: automated evaluations, re-ranking, and hallucination mitigation.

Observability

Proficiency with LLM-specific stacks: LangSmith, Langfuse, Braintrust, or W&B.

About the company

Job DescriptionCEdge has an opportunity for a Senior Software Engineer - AI Native Engineering , This role is located in St. Louis/ O’Fallon,MO. If you are ready to work alongside World Renowned Technology experts, and carry the skills below, this is the opportunity that will inevitably take your career to unbelievable levels!, CEdge Inc is an innovative IT consulting firm, and a strategic business partner. We offer IT solutions to Federal and State government, as well as, Commercial Enterprises throughout the United States. Our main objective is to create an integrity-based culture that takes pride in working as a collaborative team that focuses on growth and is driven by the desire to provide purely ethical services for both our clients and teammates.

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