API / Integration Engineer - AI Reliability Engineering
Basic Qualifications
Bachelor's degree in Systems Engineering, or a related Science, Engineering or Mathematics field, plus a minimum of 5 years of relevant experience; or Master's degree, plus a minimum of 3 years of relevant experience.
CLEARANCE REQUIREMENTS: : Department of Defense Secret security clearance is required at time of hire. Applicants selected will be subject to a U.S. Government security investigation and must meet eligibility requirements for access to classified information. Due to the nature of work performed within our facilities, U.S. citizenship is required.
Responsibilities for this Position
ROLE AND POSITION OBJECTIVES:
What You'll Own
- System integrations. Design and build connections between the AI platform and enterprise systems — ERP (Oracle, IFS), data platforms (Snowflake), PLM, MES, CRM, and legacy databases. You figure out how to get data in and push results back.
- API design and development. Build RESTful and event-driven APIs that expose enterprise data to AI services and deliver AI outputs to business applications. Clean interfaces, clear contracts, proper versioning.
- Data flow architecture. Design the data pipelines that move information between systems — batch and real-time. Handle transformation, validation, and error recovery.
- Integration reliability. Build monitoring, alerting, and automated recovery for integration points. When upstream systems change, your layer adapts or fails gracefully — it does not silently corrupt data.
- Security and compliance. Ensure all data flows meet access control, audit, and compliance requirements. You work with Cyber to get it right, but the implementation is yours.
What You Won't Own
- AI model development or prompt engineering — that's the AI Engineers' job
- Enterprise system administration — you integrate with systems, you don't manage them
- Platform architecture decisions — you implement the integration patterns the Lead Architect defines
What Makes This Role Different
- You are not plugging in connectors. You are solving interoperability problems between systems spanning decades of technology — from modern cloud APIs to legacy databases with no documentation.
- Your integrations feed AI systems that make real business decisions. Data quality and reliability are not nice-to-haves — they directly affect whether the AI works.
- You will have direct access to enterprise system teams and the authority to define integration contracts. You are not waiting on a ticket queue.
Required Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, or a related field, plus 5 years of experience; or Master’s degree plus 3 years of experience
- Production experience building API integrations between enterprise systems — ERP, CRM, data warehouses, or similar. You have connected systems that weren't designed to work together.
- Strong development skills in Python and/or Java — you write integration code, not just configure middleware
- Experience with RESTful API design, event-driven architectures, and data transformation pipelines
- Database proficiency — SQL, stored procedures, schema design. You are comfortable working with both modern data platforms and legacy relational databases.
- Experience with CI/CD pipelines, containerized deployment (Docker), and cloud platforms (AWS, Azure, or GCP)
- S. citizenship required. Department of Defense Secret security clearance is required at time of hire.
Preferred Qualifications
- Experience integrating with Oracle E-Business Suite, IFS, SAP, or similar enterprise ERP platforms
- Experience with data streaming technologies — Kafka, event buses, change data capture (CDC)
- Experience with Snowflake, Palantir Foundry, or enterprise data platforms
- Familiarity with SOA patterns, API gateways, and service mesh architectures
- Experience building integrations that serve AI/ML systems — you understand what AI services need from data (embeddings, structured context,