- Expertise in at least one RPA tools such as Automation Anywhere, UiPath , Blue Prism coupled with proficiency in programming languages (e.g., Python, Java, C#).

- Knowledge and understanding of Generative AI techniques, including deep learning, neural networks, and natural language processing.

- 6 to 10 years of relevant experience.

- Familiarity with process analysis and improvement methodologies. Excellent problem-solving skills and attention to detail.

- Ability to work collaboratively in a team environment and communicate effectively with stakeholders.

- Experience with process documentation and workflow diagramming.

- Experience in designing and implementing scalable, optimized and secure RPA solutions for enterprise-level applications.

- Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.

- Generative Adversarial Networks (GANs) : Proficiency in designing and implementing GANs to generate synthetic data, enhance training datasets, and create realistic simulations for RPA testing.

- Reinforcement Learning : Expertise in applying reinforcement learning techniques to enable RPA systems to learn from experience, make adaptive decisions, and optimize automation processes over time.

- Transfer Learning : Experience in utilizing transfer learning methodologies to leverage pre-trained models and accelerate the training process for Generative AI components within RPA solutions.

- Natural Language Generation (NLG) : Knowledge of NLG algorithms to enable RPA bots to generate human-like and contextually relevant textual content for communication and reporting.

- Explainable AI (XAI) : Understanding of XAI techniques to enhance transparency and interpretability of Generative AI models within RPA systems, ensuring accountability and compliance.

- Model Deployment and Management : Familiarity with deploying Generative AI models in production environments and managing their lifecycle, including monitoring, updates, and version control.

- Data Privacy and Ethics : Knowledge of ethical considerations and data privacy principles related to Generative AI, ensuring responsible and compliant integration within RPA solutions.

- Agentic AI : Knowledge of sentiments, Prompts, and structured input to Agent and proper Structured output from Agent

- Continuous Learning and Research : Commitment to staying updated on the latest advancements in Generative AI through continuous learning, research, and participation in relevant conferences and forums.

Responsibilities :

- Lead the design and architecture of complex RPA solutions with a focus on incorporating Generative AI technologies. Development/Coding of Proposed solution.

- 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.