Senior AI Applications Engineer - Columbia, MD

Rohde & Schwarz; Columbia (MD); Presencial; USD 140 000 - 210 000; Tempo integral

Resumo da oferta

Rohde & Schwarz in Columbia, MD is seeking an experienced AI/ML engineering leader to own technical architecture for the team's AI applications, set engineering standards, and lead junior developers.

You will deploy LLM-powered apps on Azure, build data pipelines, integrate with enterprise tools, and move prototypes to production while documenting decisions and guiding long-term support.

Responsabilidades

• Own technical architecture and implementation decisions for the team's AI applications, documenting key decisions and tradeoffs.
• Provide technical leadership to junior developers and interns, including assigning and scoping technical work, reviewing code, and guiding their growth.
• Establish engineering standards for code review, testing, CI/CD, security, and documentation.
• Set up and manage hosting, deployment pipelines, and data integrations on Azure and internal platforms.
• Build, test, deploy, and maintain LLM-powered applications and AI agents.
• Develop tools to assess, grade, and triage RFIs, solicitations, and related requests.
• Automate proposal and project artifacts, including requirements traceability matrices, CDRL deliverables, presentations, and related documentation.
• Build document-processing pipelines using OCR, structured extraction, retrieval, and other AI techniques.
• Integrate AI applications with enterprise tools, internal systems, APIs, and data sources.
• Move prototypes into production through testing, monitoring, error handling, and performance improvements, and prepare documentation and handover so solutions can be supported long term.
• Partner with the AI Lead, end users, and technical teams to assess feasibility, refine requirements, and advise on technical risks and tradeoffs.

Descrição da oferta de emprego

• Own technical architecture and implementation decisions for the team's AI applications, documenting key decisions and tradeoffs.
• Provide technical leadership to junior developers and interns, including assigning and scoping technical work, reviewing code, and guiding their growth.
• Establish engineering standards for code review, testing, CI/CD, security, and documentation.
• Set up and manage hosting, deployment pipelines, and data integrations on Azure and internal platforms.
• Build, test, deploy, and maintain LLM-powered applications and AI agents.
• Develop tools to assess, grade, and triage RFIs, solicitations, and related requests.
• Automate proposal and project artifacts, including requirements traceability matrices, CDRL deliverables, presentations, and related documentation.
• Build document-processing pipelines using OCR, structured extraction, retrieval, and other AI techniques.
• Integrate AI applications with enterprise tools, internal systems, APIs, and data sources.
• Move prototypes into production through testing, monitoring, error handling, and performance improvements, and prepare documentation and handover so solutions can be supported long term.
• Partner with the AI Lead, end users, and technical teams to assess feasibility, refine requirements, and advise on technical risks and tradeoffs.