AI Systems Engineer (Claude)
New
IndiaFull-TimeMiddle
Salary not disclosed
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Job Details
- Required Skills
- SAP
Requirements
- Proven experience as an AI Developer, AI Systems Engineer, or in a similar AI-focused engineering role.
- Hands-on expertise with Claude Code, including applying it to software analysis, requirement definition, and automation refactoring initiatives.
- Strong understanding of systems engineering principles, including technical planning, requirements gathering, system integration, validation, and lifecycle management.
- Experience translating business requirements into scalable software and systems architecture.
- Knowledge of robotic process automation (RPA) platforms and automation modernization projects.
- Strong analytical, problem-solving, and documentation skills with the ability to evaluate technical trade-offs.
- Excellent collaboration and communication abilities, with experience working across technical and business teams.
- Ability to manage multiple priorities while delivering high-quality engineering solutions in dynamic environments.
- Experience working with SAP environments is highly desirable.
Responsibilities
- Lead the technical planning and systems engineering activities required to modernize and refactor an existing portfolio of robotic process automations (RPAs).
- Define system requirements, dependencies, architecture, and implementation strategies while ensuring alignment with business objectives, technical constraints, and delivery timelines.
- Utilize Claude Code to analyze existing automation workflows, scope refactoring efforts, and develop scalable AI-assisted engineering solutions.
- Perform system analysis, functional decomposition, interface definition, trade-off evaluations, and validation activities throughout the solution lifecycle.
- Collaborate closely with engineering, automation, and business stakeholders to convert customer and operational requirements into effective software and system specifications.
- Support system integration, verification, validation, and continuous improvement initiatives to ensure reliable, maintainable, and high-performing automation platforms.
- Identify technical risks, recommend mitigation strategies, and contribute to the evolution of AI-driven automation capabilities across enterprise systems.
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