Automation Engineer

 

Qualifications

1.Bachelor s or Master s degree in Computer Science, Engineering, or a related field.

2.3 to 8 years of relevant experience.

3.Proven experience as Solution Architect or Lead, with a strong emphasis on integrating Generative AI into solutions or exposure to Machine Learning.

4.Good to have expertise in at least one RPA tools such as Automation Anywhere, UiPath , Blue Prism, Power Automate coupled with proficiency in programming languages (e.g., Python or Java).

Skills

1.Hands-on programming and architecture capabilities in Python or Java

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

3.Strong experience with statistical packages and machine learning libraries (e.g., R, Python scikit-learn, Spark MLlib)

4.Hands on experience with RDBMS, NoSQL.

5.Must have Experience in Cloud Platforms like AWS/AZURE/GCP

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

7.Familiarity with process analysis and improvement methodologies.

8.Experience with technical documentation and workflow diagramming.

9.Proven experience in designing and implementing scalable, optimized and secure automation solutions for enterprise-level AI solutions.

10.Strong expertise in Generative AI technologies (RAG,LLM,AI Agent).

11.Advanced Python programming skills with expertise in (Good to have at least 1):
o Deep Learning frameworks (PyTorch/TensorFlow/Keras)
o ML libraries (scikitlearn/pandas/numpy)
o NLP libraries (spaCy/ NLTK/ Hugging Face Transformers)
o LLM frameworks (langchain/llamaindex)

Responsibilities

1.Lead the design and architecture of complex RPA solutions focusing on incorporating Generative AI technologies. Development/Coding.

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

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

4.Take technical ownership of end-to-end engagement as he/she would be completely responsible for the same.

5.Lead and mentor a team of senior developers and engineers in implementing AI solutions.

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

7.Stay current with emerging technologies, particularly in Generative AI, and evaluate their potential impact on RPA strategies.

8.Demonstrate adaptability and flexibility in technologies, work environment and work timing as we work with global customers.

9.Accurately estimate project efforts and timeline during project initiation with appropriate risk, dependency and constraints.

10.Willingness to work from client locations or AA offices as required.