Sr. Agentic Software Engineer

Title: Sr. Agentic Software Engineer

Location: Charlotte NC (3-4x onsite a week)

Duration: 5 Months Contract to hire

Job Description:

• • • Most important thing to Manager is finding quality strong/seasoned engineers
    • He is not expecting someone to come in with 10 years of experience building agents on the AI front
    • Needs to have a solid understanding of AI coupled with strong foundational coding skills
    • Need great people in the following areas: Compute CD Support Eng Dev Prod Automation & Agentic
    • Compute peeps might be stronger in DevOps/less coding - he would be open to considering that as well
    • Manager has found it very challenging to find people with decent programming skills (GoLang Python Typescript)
    • Each product has their own tech stack/language - if we find someone really solid in one area he could likely find a place for them
    • He understands that a lot of individuals are using AI for coding (and transparently they do some of that at client as well) - however they are looking for individuals with true foundational skills & those without will not perform well on the coding assessment
    • For the Agentic AI openings he is not expecting someone to come in with 10 years of experience building AI agents he is focused on finding strong engineers with a solid understanding of AI (a few years of hands-on experience should be enough)
    • We are seeking a Senior Agentic Software Engineer to design build and operate production-grade AI agent systems that augment and automate real business workflows.
    • This role goes beyond prompt engineering or demo-level prototypes. You will own agentic systems end-to-end-from architecture and integration with existing services to reliability evaluation and long-term operation. Youll work closely with product platform and domain experts to deliver agentic capabilities that are trustworthy scalable and measurable while helping define how agentic systems are built across the organization.

What Youll Do

• • • Design build and operate agentic systems that reliably complete real tasks not just answer questions.
    • Architect agents that support planning memory tool use and multi-step execution selecting appropriate patterns (single-agent multi-agent workflow-driven human-in-the-loop) based on problem constraints and risk.
    • Balance autonomy with control by designing agents that are predictable debuggable secure and aligned with business goals.
    • Build agents using modern frameworks (e.g. LangGraph LangChain Semantic Kernel AutoGen or equivalent) implementing structured outputs tool-calling reflection and state management.
    • Design and implement MCP- and/or RAG-based integrations as first-class mechanisms for how agents access tools data and context.
    • Enforce security consent access control and observability across all agent tool interactions partnering with platform teams to establish and evolve MCP integration standards.
    • Integrate agentic systems into existing services and platforms via APIs and backend services owning production readiness end-to-end.
    • Define what good looks like for agents using clear metrics (e.g. accuracy success rate latency cost failure modes) and use those metrics to drive continuous improvement.
    • Build automated evaluation pipelines (offline tests synthetic data regression checks) and instrument agents with tracing logging and observability to support debugging and iteration in production.
    • Design fallback recovery and human-escalation mechanisms for failure scenarios proactively identifying and mitigating failure modes.
    • Establish architectural standards and best practices for agentic development raising the technical bar through design reviews documentation mentorship and knowledge sharing.
    • Partner with product and domain stakeholders to shape solutions make informed trade-offs and ensure agentic systems deliver meaningful business impact.

Domain / Problem Space

• • • You will work on agentic systems in the context of:
    • Experience with internal developer portals like Backstage with associated patterns like GitOps API-driven microservices paved paths and more
    • Experience with design patterns in Kubernetes like controllers control planes operators and more
    • Work on container orchestration infrastructure as code (IaC) and CI/CD pipelines for deploying and managing k8s instances.
    • Monitor the performance of developer platform identify potential issues and ensure high availability of the platform.
    • Using Infrastructure As Code (IAC) best practices create automated infrastructure within the cloud and on-premise platform including package management application load and configuration and systems monitoring and administration.
    • Deliver improvements to source code management deployment operations maintenance cost control security monitoring and audit tools and processes.
    • Implement and maintain CI/CD tools and processes to support development QA and customer value realization teams.
    • Manage a service critical codebase with version control using Git including Gitlab or Github
    • These domains require agents that operate on real evolving data integrate deeply with existing systems and meet a high bar for correctness traceability and user trust.

Required Experience

• • • 5 years of professional software engineering experience with a strong backend or systems background.
    • Proven experience building LLM-powered applications beyond prototypes.
    • Hands-on experience designing and implementing agentic systems including agents workflows MCP-based tool integration and RAG.
    • Strong proficiency in Python (or similar agent-oriented languages) and experience building production APIs or services.
    • Experience designing systems with observability evaluation and operational ownership in mind.