Lead Agentic Software Engineer

Reingold Inc•Alexandria, VA

3d•$120,700 - $193,100•Hybrid

About The Position

Reingold is seeking a Lead Agentic Software Engineer to build the platforms our clients run on — content management systems, e-commerce, web applications, and integrations — and to bring AI agents and automation into that work for our government, nonprofit, and commercial clients. This is a full-time, exempt position in Reingold’s Digital department, reporting to the Senior Director, Digital. You’ll spend most of your time as a hands-on, billable engineer on client projects: architecting and shipping production applications and platform builds, and applying agentic AI — LLM-powered agents that plan, call tools, and carry out multi-step work — to client products, delivery pipelines, and internal operations. The rest is reserved for capability building: evaluating emerging AI tools and models, developing reusable components and internal tooling, and setting engineering and quality standards that scale across teams. It’s a senior individual-contributor role that blends deep platform engineering with practical, production-grade AI. This is a hybrid role, requiring at least two days per week on site at Reingold’s headquarters in Alexandria, VA.

Requirements

Bachelor’s degree in computer science, software engineering, information systems, or a related field, or equivalent professional experience, with seven or more years building and shipping production web applications and platforms.
Deep experience delivering and maintaining sites or applications on one or more enterprise content management platforms — for example WordPress, Umbraco/.NET, Adobe Experience Manager, or a headless CMS — with a track record of picking up unfamiliar platforms quickly.
Strong full-stack experience with modern JavaScript frameworks (React, TypeScript), API design, and both relational and NoSQL databases.
Hands-on experience engineering e-commerce solutions, including storefront, checkout and payment integration, catalog or order management, and reporting.
Production experience building with large language models — API integration, prompt engineering, retrieval-augmented generation, and agent or workflow automation — deployed to real users, not just prototypes.
Experience designing and implementing automated testing, including end-to-end or regression suites in CI pipelines.
Clear technical communication, in writing and in person, with both technical and non-technical audiences.
U.S. citizenship, with the ability to obtain and maintain a U.S. government suitability or clearance determination if required for a project assignment.

Nice To Haves

Experience with cloud AI services such as Google Vertex AI, Azure AI, or Amazon Bedrock.
Experience delivering software in federal, state, or nonprofit environments, including work subject to security review, authority to operate (ATO) processes, or Section 508 compliance.
Familiarity with the Model Context Protocol (MCP), vector databases, and agent evaluation or observability tooling.
Experience with headless and decoupled architectures, including headless CMS platforms and front-end frameworks such as Next.js.
Experience with DevOps practices and infrastructure as code, such as Terraform, Docker, and GitHub Actions.
Depth in one or more enterprise commerce or experience platforms at scale — such as Adobe Commerce (Magento), Shopify Plus, Salesforce Commerce Cloud, or Adobe Experience Manager — and familiarity with PCI DSS and secure handling of payment data.
Experience contributing to proposals, technical scoping, or estimates, and presenting technical work to clients.

Responsibilities

Bring AI agents and automation into client products, delivery pipelines, and internal operations — architecting agentic systems end to end: model and framework selection (e.g., Anthropic, OpenAI), tool and function calling, multi-step orchestration, context and memory, retrieval-augmented generation with embeddings and vector stores, and guardrails and fallback behavior — choosing approaches based on accuracy, latency, and cost.
Design, build, and ship production web applications, platforms, and integrations for client programs — architecting the full stack across modern JavaScript frameworks (React, TypeScript), server-side services, and relational and NoSQL data stores.
Define and run evaluations of agent behavior — task success, tool-call correctness, regression, reliability, and cost — and iterate on production systems based on measured results, holding the work to a real production bar rather than demos.
Establish responsible-AI and data-governance practices for public-sector and regulated work: secure handling of client data, human-in-the-loop review, and safeguards against hallucination, prompt injection, data leakage, and inappropriate disclosure.
Lead architecture and development on enterprise content management platforms — traditional and headless alike, including WordPress, Umbraco/.NET, Adobe Experience Manager, and comparable systems — and integrate them with AI services, third-party APIs, and client data.
Design and build e-commerce solutions on platforms such as Adobe Commerce, Shopify, or WooCommerce: storefront, catalog and order management, checkout and payment integration, and connections to fulfillment, CRM, and analytics.
Deploy and operate applications on a major cloud platform: CI/CD pipelines, containerized or serverless services, monitoring, and cost management.
Own quality on your work: build automated end-to-end, regression, and API test suites (for example with Playwright or Cypress) with CI quality gates, and implement automated accessibility testing against Section 508 and WCAG 2.1 AA (for example with axe or WAVE), leading remediation — applying AI-assisted techniques such as test generation, visual regression, and defect triage where they help.
Evaluate emerging AI platforms, models, and tools — including agentic coding tools such as Claude Code, Cursor, and GitHub Copilot — recommend adoption based on testing in real Reingold workflows, and build reusable components and internal tooling that teams can apply across engagements.
Partner with strategists, designers, account teams, and clients to turn business goals into technical requirements and explain tradeoffs to non-technical audiences — providing technical direction and code review on projects, acting as technical lead when we’re building agentic tooling for a client, and mentoring developers and sharing what you learn across the agency.