OverviewAllspring Engineering and Technology is seeking an Application Engineer with AI skills to build and enhance the technology platforms supporting Marketing and Distribution, with a particular focus on agentic automation. The engineer will initially work on Allspring's production agentic RFP/DDQ platform and will help develop new agentic capabilities and platforms as additional business use cases emerge.
Working within the Client Journey Management Technology team, the engineer will partner with Engineers, Application Strategists, Product Owners, and QA Analysts across the full application lifecycle, from development and enhancement through production support and continuous improvement.
The ideal candidate brings strong Python engineering skills, experience supporting production applications, and hands-on exposure to LLM-based solutions, with an interest in building scalable agentic applications and taking increasing ownership of the platforms.
We currently operate in a hybrid working model, whereby you will be required to work in-office 4 days per week.
Location(s): Charlotte, NC, or Milwaukee, WI
ResponsibilitiesEngineering & Platform Delivery- Design, build, enhance, and support technology platforms that enable Allspring's Marketing and Distribution capabilities, with an increasing focus on AI and agentic automation.
- Develop scalable, maintainable solutions across Python services, APIs, integrations, and React/TypeScript applications.
- Build and enhance agentic capabilities, initially supporting the RFP/DDQ platform while extending reusable AI patterns and capabilities to other Marketing and Distribution use cases.
- Integrate CJM platforms with business applications, enterprise services, content repositories, and data sources.
- Partner with Application Strategists, Product Owners, QA Analysts, fellow Engineers, and business stakeholders to translate business needs into sustainable technology solutions.
- Follow established engineering practices for development, code review, testing, deployment, documentation, and production readiness.
Operations & Technical Support- Monitor application health and performance across pre-production and production environments, including CloudWatch alarms and Arize Phoenix traces.
- Triage application alerts and user-reported issues, diagnose root causes, implement fixes, and escalate complex issues with clear technical analysis.
- Investigate AI answer-quality issues by evaluating source retrieval, content, prompts, configuration, and application code.
- Deliver bug fixes, technical improvements, and application enhancements as part of the ongoing engineering lifecycle.
- Maintain runbooks, technical documentation, and known-issues tracking to improve platform reliability and supportability.
- Participate in the team's established production support and escalation model as required
Agentic AI, Knowledge & Content- Manage document ingestion and synchronization for the Bedrock Knowledge Base as underlying content changes.
- Validate metadata, provenance, and citations following content ingestion.
- Partner with business and content owners to identify content-quality or freshness issues that may affect agentic platform responses.
- Develop and refine prompts, configurations, retrieval approaches, and other components that improve the accuracy and effectiveness of agentic solutions.
- Run appropriate evaluations against established datasets before AI-related changes are released.
Quality & Engineering Excellence- Build and maintain automated unit, integration, and end-to-end testing across backend and frontend components.
- Maintain application dependencies and container images, proactively identifying potential breaking changes or technical risks.
- Support model and platform upgrades through regression testing, impact analysis, and documentation.
- Help strengthen observability, resiliency, security, maintainability, and production readiness across CJM applications.
- Monitor platform usage and cloud costs and identify unusual trends or opportunities for optimization.
QualificationsRequired Qualifications- 2-4 years of professional software engineering experience, including hands-on development of production applications using Python.
- Experience with or strong understanding of LLM-powered applications, including model APIs, prompt design, evaluating LLM output quality, and RAG concepts such as embeddings, retrieval, grounding, and citations.
- Working knowledge of AWS services such as ECS, SQS, S3, and CloudWatch and experience with PostgreSQL; exposure to Amazon Bedrock is highly desirable.
- Experience with modern software engineering practices, including Git, pull-request workflows, automated testing, and production deployment and support.
- Working knowledge of React and TypeScript, with the ability to contribute across backend and frontend components.
- Strong analytical and troubleshooting skills, including the ability to interpret logs, reproduce issues, identify root causes, and clearly document findings.
- Strong attention to accuracy, quality, traceability, and controls, particularly when developing and supporting applications in a regulated environment.
- Strong written and verbal communication skills, with the ability to work effectively with both technical teams and business stakeholders.
- Ability to collaborate across engineering, product, QA, and business teams to translate business needs into reliable, scalable technology solutions.
- Ability to work independently and collaboratively in a cross-functional environment.
- Ability to work at a computer and use standard business software for extended periods during the workday.
- Communicate effectively with colleagues, clients, and business partners in person and electronically as needed.
- Engage in regular in-person interaction and collaboration with team members and other stakeholders.
- Work effectively in a professional office environment with ongoing collaboration, activity, and shifting priorities.
- Maintain productivity and focus while balancing multiple tasks and interruptions common in an in-person business setting.
Preferred Qualifications- Experience with agentic AI frameworks such as Claude Agent SDK, LangGraph, LangChain, or similar technologies.
- Experience with LLM evaluation, observability, and tracing tools such as Arize Phoenix.
- Familiarity with containerization, infrastructure-as-code, and CI/CD technologies such as Docker, Terraform, and Jenkins.
- Experience using AI-assisted software development tools, such as Claude Code, within structured engineering and code-review practices.
- Hands-on experience with Anthropic models, Claude Agent SDK, Amazon Bedrock, or comparable enterprise AI technologies.
- AWS certification, such as Cloud Practitioner, Developer, or AI Practitioner, is a plus.
- Experience developing or supporting technology solutions within financial services or another regulated industry.
Please note: This position does not offer sponsorship for employment visas. Applicants must be legally authorized to work in The United States without sponsorship now or in the future.
CompensationBase Pay Range: $120,000 - $130,000
Actual base salary may vary based upon, but not limited to, relevant experience, time in role, base salary internal peers, prior performance, business sector, and geographic location. In addition to base salary, the competitive compensation package may include, depending on the role, participation in an incentive program linked to performance (for example, annual discretionary bonus programs, or other annual or non-annual incentive or sales plans.)
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