The Role
Build agentic workflows, Retool applications, and data integrations for enterprise AI solutions. Develop connectors and pipelines to vector stores, ensure data quality, integrate models via MCP, implement API/SQL-based apps, and collaborate on runbooks and documentation to deploy scalable AI CTRL solutions for clients.
Summary Generated by Built In
Join Expedient's AI CTRL product team as an AI Engineer where you'll build the agentic workflows, Retool applications, and data integrations that turn enterprise AI services into working, deployed solutions for our clients. You'll work hands-on with the full AI CTRL stack alongside a team of AI developers. Deep AI research background isn't required — bring your development expertise, Python instincts, and curiosity to scale out.
What You'll Do:
What You'll Do:
- Design & Build Agentic Workflows:** Develop and maintain automated workflows using tools that support the AI CTRL Agentic Workflow Engine (AWE) that execute multi-step client business processes end-to-end
- Build Client-Facing Applications:** Create apps for internal ops and client use cases — workflow catalogs, usage dashboards, billing reporting, automation, and custom AI-powered tools
- Integrate Enterprise Systems:** Design, configure and maintain MCP (Model Context Protocol) server integrations connecting AI models
- Build Data Connector Pipelines:** Develop connectors between client data sources and the vector store; ensure data flows correctly into AI-ready formats
- Ensure Data Quality:** Implement validation and cleansing processes that directly impact AI model accuracy
- Collaborate & Document:** Partner with the AI Dev engineering team on platform improvements, runbooks, integration guides, and workflow documentation at scale
- 2–4 years in software development, systems integration, AI/automation engineering, or a closely related technical role. Prior experience at a managed service provider, SaaS company, or enterprise technology team is a strong plus.
- Building apps, workflows, database queries, REST API connections, and JavaScript transforms — able to deliver without engineering hand-holding
- Working knowledge of LLM APIs (Anthropic Claude, OpenAI, Google Gemini): prompt construction, tool use/function calling, token management
- Python scripting: automation, file processing, API calls, JSON handling
- REST API consumption and light API development (FastAPI or equivalent)
- SQL fundamentals — can write queries for reporting and Retool data connections
- Familiarity with **RAG concepts**: chunking, embedding, vector search, context window management
- Kubernetes basics: reading pod logs, understanding namespace structure, construct of containers
- Understanding of SSO/OIDC at a configuration level (Entra ID, Okta, OneLogin
- Self-directed: picks up a backlog item, researches an unfamiliar connector API, and delivers working code
- Documentation instinct: writes the runbook before calling something done; updates the guide when the process changes
- PM-adjacent thinking: understands that a feature isn't done when the code works — it's done when the client can use it without a support ticket
- Optimize & Innovate: Troubleshoot pipeline issues, enhance performance, and stay current with emerging data engineering technologies
- Adaptable in fast-paced environments, strong ownership mentality, entrepreneurial mindset, excellent communicator, passionate about solving business problems with data
- Bachelor's in Computer Science, Engineering, Information Systems, or related field (or equivalent practical experience
Location & Compensation:
Indianapolis, Cleveland, Pittsburgh, Columbus, or Memphis. Hybrid work model. Regional travel may be required.
Salary for this position is directly related to your own experience, knowledge, and skills. Estimated range for this role is $120,000 to $150,000
#LI-hybrid
Indianapolis, Cleveland, Pittsburgh, Columbus, or Memphis. Hybrid work model. Regional travel may be required.
Salary for this position is directly related to your own experience, knowledge, and skills. Estimated range for this role is $120,000 to $150,000
#LI-hybrid
Skills Required
- 2-4 years in software development, systems integration, AI/automation engineering, or related technical role
- Experience building apps, workflows, database queries, REST API connections, and JavaScript transforms
- Working knowledge of LLM APIs (Anthropic Claude, OpenAI, Google Gemini), including prompt construction, tool use/function calling, and token management
- Python scripting for automation, file processing, API calls, and JSON handling
- REST API consumption and light API development experience (FastAPI or equivalent)
- SQL fundamentals and ability to write queries for reporting and Retool data connections
- Familiarity with RAG concepts: chunking, embeddings, vector search, and context window management
- Kubernetes basics: reading pod logs, understanding namespaces and container constructs
- Understanding of SSO/OIDC configuration (Entra ID, Okta, OneLogin)
- Experience with Retool applications and building client-facing internal ops apps
- Strong self-direction, documentation/runbook writing, and client-focused product delivery mindset
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent practical experience
- Prior experience at a managed service provider, SaaS company, or enterprise technology team
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The Company
What We Do
Expedient is a network of data centers offering cloud computing, a wide range of managed services, and network connectivity.
