Solution Architect

Role & responsibilities

1. Bachelors or Masters degree in Computer Science, Engineering, or a related field.

2. Proven experience as an RPA Solution Architect

   , with a strong emphasis on integrating Generative AI into automation solutions.

3. 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#).

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

5. 6 to 10 years of relevant experience.

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

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

8. Experience with process documentation and workflow diagramming.

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

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

11. Generative Adversarial Networks (GANs):

    Proficiency in designing and implementing GANs to generate synthetic data, enhance training datasets, and create realistic simulations for RPA testing.

12. 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.

13. 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.

14. 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.

15. Explainable AI (XAI):

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

16. Model Deployment and Management:

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

17. Data Privacy and Ethics:

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

18. Agentic AI:

    Knowledge of sentiments, Prompts, and structured input to Agent and proper Structured output from Agent

19. 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:

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

1. Collaborate with stakeholders to understand business requirements and align automation strategies with organizational goals.

2. Develop high-level and detailed solution designs, ensuring they meet scalability, reliability, and security standards.

3. Technical ownership of end-to-end engagement as he/she would be completely responsible for the same.

4. Integrate Generative AI capabilities into RPA solutions to enhance customer deliverable, decision-making, learning, and adaptive automation processes.

5. Provide technical leadership and guidance to RPA development teams throughout the project lifecycle.

6. Conduct feasibility studies and assess the applicability of Generative AI algorithms to optimize automation outcomes.

7. Stay abreast of emerging technologies, especially in Generative AI, and evaluate their potential impact on RPA strategies.

8. Adaptability and flexibility with respect to technologies, work environment and work timing as we work with global customers.

9. Ability to accurately estimate project efforts and timeline during project initiation with appropriate risk, dependency and constraints.

11. Open to work from client location and AA office.