Senior Agentic Software Engineer

Eliassen Group; Charlotte (NC); Hybrid; USD 136,000 - 157,000; Full time

Benefits offered by this job

Medical, Dental, Vision benefits

401k with company matching

Life insurance

Job summary

Eliassen Group is seeking a Senior Agentic Software Engineer in Charlotte, NC for a hybrid role blending on-site collaboration with remote flexibility.

You will design and deliver intelligent systems combining AI agents, cloud services, and automation frameworks, while applying disciplined engineering practices, TDD, code reviews, and security controls. Experience with AWS/Azure, and agent architectures is preferred.

Qualifications

• 5+ years designing and delivering enterprise software in fast-paced environments.
• Strong fundamentals in data structures, algorithms, design patterns, SOLID, and testing.
• Experience with API design, distributed systems, and AI-assisted or agent-generated code.

Responsibilities

• Design and implement agentic AI solutions using modern LLMs, AI agents, MCP integrations, and cloud-native services.
• Build production-ready AI-enabled applications on AWS and Azure, including agent runtimes like AWS AgentCore.
• Create reusable frameworks, accelerators, templates, and patterns to increase delivery capacity.
• Balance autonomous agent behavior with human oversight, governance, and security controls.
• Apply disciplined engineering practices: clean architecture, testing, documentation, and maintainable code.
• Lead Spec-Driven Development and collaborate with product owners on estimates and risk.

Skills

C#

Java

Python

TypeScript

Go

Tools

GitHub Copilot

Claude Code

Kiro

OpenSpec

Job description

Description:

Hybrid 3 days on-site in Charlotte, NC

Our client seeks a Senior Agentic Software Engineer who will design and deliver intelligent systems that combine AI agents, cloud-native architectures, automation frameworks, and modern engineering practices. The role will build and scale agentic AI solutions, accelerate delivery through Spec-Driven Development, and create reusable frameworks that improve speed, safety, and quality. The environment is fast paced with shifting priorities and minimal supervision, requiring disciplined engineering, independent ownership, and clear communication.

Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $99.00 to $114.00/hr. w2

Responsibilities:

• Design and implement agentic AI solutions using modern LLMs, AI agents, MCP integrations, orchestration frameworks, and cloud-native services.
• Build production-ready AI-enabled applications on AWS and Azure, including agent runtimes such as AWS AgentCore.
• Create reusable frameworks, accelerators, templates, and patterns to increase delivery capacity.
• Balance autonomous agent behavior with human oversight, governance, and security controls.
• Apply disciplined engineering practices including clean architecture, design patterns, test coverage, documentation, and maintainable code.
• Practice TDD, refactoring, CI, and methodical debugging with root-cause analysis.
• Perform thorough code reviews for human-written and agent-generated code with focus on correctness, security, performance, and maintainability.
• Identify and remediate defects common in agent output, including hallucinated APIs, weak error handling, insecure patterns, duplication, and ineffective tests.
• Lead Spec-Driven Development, translating goals into clear, testable specifications and improving SDD practices and tooling.
• Partner with product owners on estimation, feasibility, tradeoffs, risk identification, and re-planning as priorities shift.
• Design and implement APIs, MCP servers, integrations, and event-driven or service-oriented architectures.
• Integrate enterprise systems, knowledge repositories, and workflows into agentic ecosystems and contribute to platform standards.
• Mentor junior engineers and upskill teams in SDD, agentic engineering, and software fundamentals.
• Communicate clearly with stakeholders and provide proactive status, risks, and blockers.

Experience Requirements:

• 5+ years designing, building, and delivering enterprise software to production with a proven record in fast-paced environments.
• Ability to work independently with minimal supervision and own outcomes end to end; portfolio preferred.
• Expert fundamentals in data structures, algorithms, design patterns, SOLID, clean code, testing strategies, and refactoring.
• Proficiency in one or more languages such as C#, Java, Python, TypeScript, or Go.
• Deep understanding of API design and distributed systems.
• Strong experience with automated testing including unit, integration, and contract testing, and with TDD.
• Experience managing and optimizing databases.
• Extensive code review experience and ability to validate AI-assisted and agent-generated code using tools such as GitHub Copilot, Claude Code, Kiro, or OpenSpec.
• Hands-on experience with Spec-Driven Development and translating complex problems into structured specifications.
• Cloud experience on AWS and/or Azure, with knowledge of agent architectures, orchestration frameworks, MCP, tool integrations, and human-in-the-loop workflows.
• Experience with event-driven architectures, serverless, containers, CI/CD, and Infrastructure as Code; able to set up CI/CD independently.
• Familiarity with observability, telemetry, and operational monitoring.
• Product collaboration experience for estimates, feasibility, and technical tradeoffs on cross-functional teams.
• Security knowledge including authentication, authorization, encryption, secure SDLC, and mitigation of risks such as SQL injection, DoS, and XSS, with attention to AI-generated code.
• Preferred: experience with AWS AgentCore; frameworks such as Strands, LangChain, Semantic Kernel, AutoGen, or CrewAI; building MCP servers and tool ecosystems; designing agents for enterprise workflows; creating engineering standards and reusable frameworks; evaluating emerging AI technologies for enterprise use.