Senior Agentic AI Engineer

Senior Agentic AI Engineer

Location:  Charlotte, NC (Hybrid)
Duration:  12 Month Contract

Overview:
We are looking for experienced, highly disciplined software engineers who are passionate about redefining how software is built through AI, automation, and Spec-Driven Development (SDD).

Our team builds and scales agentic AI solutions, accelerates software delivery through SDD, and creates reusable frameworks that help product teams build software faster, safer, and with higher quality.

Senior Agentic Software Engineers design and deliver intelligent systems that combine AI agents, cloud-native architectures, automation frameworks, and modern software engineering practices. This role requires proven industry experience delivering production software, a strong foundation in software engineering fundamentals, and the discipline to apply those fundamentals rigorously when working alongside AI coding agents.

Work Environment:  

This is a fast-paced role with tight deadlines and priorities that can shift quickly. We need someone who thrives in this type of environment: an engineer who can pivot without losing momentum, re-plan quickly when direction changes, and keep delivering high-quality work under time pressure.

This role operates with minimal supervision. You will be expected to take ownership of your work, make sound technical decisions on your own, manage your own priorities, and proactively raise risks and blockers without waiting to be asked.

Responsibilities:  

Agentic Solution Design & Development

• Design and implement complex 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.
• Develop reusable frameworks, accelerators, templates, and engineering patterns that increase delivery capacity across teams.
• Design systems that balance autonomous agent behavior with human oversight, governance, and security controls.

Software Engineering Fundamentals & Discipline

• Apply strong engineering discipline to every deliverable: clean architecture, sound design patterns, meaningful test coverage, clear documentation, and maintainable code.
• Hold AI-assisted and agent-generated work to the same standards as human-written code. Speed from AI tools never replaces engineering rigor.
• Practice TDD, refactoring, and continuous integration as everyday habits rather than optional steps.
• Debug methodically, identify root causes, and build solutions that prevent recurring problems.
• Proactively manage technical debt and protect the long-term health of the codebase.

Code Review (Including Agent-Generated Code)

• Perform thorough, high-quality code reviews for both human-written and agent-generated code.
• Critically evaluate AI-generated code for correctness, security, performance, maintainability, test quality, and alignment with the specification and architecture.
• Identify subtle defects common in agent output, such as hallucinated APIs, incomplete error handling, insecure patterns, over-engineering, duplicated logic, and tests that pass without validating real behavior.
• Set and model review standards for the team and coach others on how to review agent-generated code effectively.

Spec-Driven Development (SDD)

• Lead software delivery using Spec-Driven Development methodologies.
• Translate business goals and user needs into clear, structured specifications that drive AI-assisted and agentic development workflows.
• Review and refine specifications to make sure they are complete, testable, and implementation-ready before work begins.
• Continuously improve SDD practices, tooling, templates, and engineering standards.

Product Partnership, Estimation & Feasibility

• Partner closely with product owners to shape work, providing realistic estimates and candid feasibility feedback early in the process.
• Identify technical risks, dependencies, and constraints, and propose options and tradeoffs that help product make informed decisions.
• Break complex ideas into right-sized user stories and deliverable increments.
• Re-estimate and re-plan quickly when priorities or scope change.

Platform & Integration Engineering

• Design and implement APIs, MCP servers, integrations, and service interfaces that give AI agents secure access to tools.
• Build event-driven and service-oriented architectures.
• Integrate enterprise systems, knowledge repositories, APIs, and business workflows into agentic ecosystems.
• Contribute to enterprise AI platform evolution and architecture standards.

Mentoring & Upskilling

• Mentor junior engineers through pairing, code reviews, design discussions, and hands-on coaching.
• Help upskill the broader team in SDD, agentic engineering, AI-assisted development, and core software engineering fundamentals.
• Share knowledge through demos, documentation, brown bags, and communities of practice.

Communication

• Communicate clearly and concisely with engineers, product owners, architects, and leadership, both in writing and verbally.
• Provide proactive, transparent status updates, including risks, blockers, and changes in direction.
• Explain complex technical concepts and tradeoffs in plain language for non-technical audiences.

Required Qualifications: 

Industry Experience

• 5+ years of professional industry experience designing, building, and delivering enterprise software solutions to production.
• Proven track record of delivering in fast-paced environments with tight deadlines and shifting priorities.
• Demonstrated ability to work independently with minimal supervision and own outcomes end to end.
• Portfolio of work (code samples, repositories, or project examples) preferred.

Software Engineering Fundamentals

• Expert-level command of software engineering fundamentals: data structures, algorithms, design patterns, SOLID principles, clean code, testing strategies, and refactoring.
• Strong proficiency in one or more modern programming 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 practices.
• Experience managing and optimizing databases.

Code Review & AI-Assisted Development

• Extensive code review experience with a demonstrated ability to give clear, actionable, constructive feedback.
• Hands-on experience reviewing and validating code produced by AI coding agents and AI-assisted tools such as GitHub Copilot, Claude Code, Kiro, OpenSpec, or similar platforms.
• Hands-on experience with Spec-Driven Development concepts and workflows.
• Ability to break down complex business problems into structured specifications and implementation plans.

Cloud & Agentic Development

• Experience building production solutions on AWS and/or Azure.
• Understanding of AI agent architectures, orchestration frameworks, MCP, tool integration patterns, and human-in-the-loop workflows.
• Experience with event-driven architectures, serverless computing, containers, CI/CD pipelines, and Infrastructure as Code.
• Ability to set up CI/CD for new products without guidance.
• Familiarity with observability, telemetry, and operational monitoring.

Product Collaboration

• Proven experience working directly with product owners to provide estimates, feasibility assessments, and technical tradeoff recommendations.
• Experience collaborating on cross-functional product teams.

Communication & Mentorship

• Excellent written and verbal communication skills.
• Demonstrated experience mentoring junior engineers and upskilling teams.

Security & Governance

• Strong understanding of security principles, including authentication, authorization, encryption, and secure software development.
• Knowledge of common attack vectors (such as SQL injection, DoS, and XSS) and how to mitigate them, with particular attention to vulnerabilities introduced by AI-generated code.
• Ability to design AI-enabled solutions that meet governance, compliance, and risk management requirements.

Preferred Qualifications:  

• Experience building or operating solutions using AWS AgentCore (strongly preferred).
• Experience with Strands, LangChain, Semantic Kernel, AutoGen, CrewAI, or similar orchestration frameworks.
• Experience implementing MCP servers and tool ecosystems.
• Experience designing AI agents that interact with enterprise systems and business workflows.
• Experience creating engineering standards, reusable frameworks, or internal developer platforms.
• Experience evaluating emerging AI technologies and turning them into practical enterprise solutions.