Systems Integration Engineer securing and enhancing unmanned systems for Navy and Marine Corps operations. Collaborating with teams to implement advanced cybersecurity measures and conduct risk assessments.
About the role
- Solution Architect leading design and architecture of RPA solutions with Generative AI at Automation Anywhere. Collaborating with stakeholders to align automation strategies with organizational goals.
Responsibilities
- Lead the design and architecture of complex RPA solutions with a focus on incorporating Generative AI technologies.
- Collaborate with stakeholders to understand business requirements and align automation strategies with organizational goals.
- Develop high-level and detailed solution designs, ensuring they meet scalability, reliability, and security standards.
- Technical ownership of end-to-end engagement as he/she would be completely responsible for the same.
- Integrate Generative AI capabilities into RPA solutions to enhance customer deliverable, decision-making, learning, and adaptive automation processes.
- Provide technical leadership and guidance to RPA development teams throughout the project lifecycle.
- Conduct feasibility studies and assess the applicability of Generative AI algorithms to optimize automation outcomes.
- Stay abreast of emerging technologies, especially in Generative AI, and evaluate their potential impact on RPA strategies.
- Adaptability and flexibility with respect to technologies, work environment and work timing as we work with global customers.
- Ability to accurately estimate project efforts and timeline during project initiation with appropriate risk, dependency and constraints.
- Open to work from client location and AA office.
Requirements
- 5-8 years of experience in software development, with at least 3 years proven experience as an RPA Solution Architect, with a strong emphasis on integrating Generative AI into automation solutions.
- Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-Learn, etc.) and cloud AI services (AWS SageMaker, Google Vertex AI, Azure ML, etc.).
- Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field.
- AI/ML certifications (e.g., Google Professional Machine Learning Engineer/AWS Certified AI Practitioners/Microsoft AI-900, etc.) preferred.
- Cloud certifications (AWS, Azure, Google Cloud) relevant to AI/ML solutions.
Job title
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