Automation Architect

Position Overview

Are you passionate about using machine learning to solve complex business problems? Do you thrive in a collaborative and innovative work environment?

As a Solution Architect Automation, you'll work in agile mode with FBS lean methodology to manage the infrastructure tools and platform that supports development and deployment of ML/DS models (DevOps/MLOps) & process Automation (UiPath). Engage a team of Automation Engineers and lead the execution of a new Intelligent automation initiatives. Build and invent customer-centric automated solutions to improve productivity and speed while reducing defects. Champion lean process simplification for O2C, R2R & P2P by identifying automation opportunities. Partner with multiple technology teams in different operating companies to facilitate seamless automation. Drive adoption of Intelligent automations and develop and present ideas for continuous improvement and investment. Showcase capabilities, cultivate use-cases and drive adoption of intelligent automations while staying current with industry and best practices. You'll also collaborate closely with cross-functional teams including data scientists, software engineers, and product managers to understand business requirements and translate them into efficient and effective data pipelines and get them ready for modelling. Design a deployment strategy for the model into existing native infrastructure and model deployment. With your expertise in machine learning algorithms, data structures, and statistics, you'll develop and implement algorithms for data mining, feature selection, predictive modeling and integrate with Process automation initiatives. This is a role for someone who is motivated to work in a fast-paced and dynamic environment, with opportunities for career growth and development, a competitive salary and benefits package, and the chance to make a real impact by driving business outcomes and delivering value.
Responsibilities and Deliverables
- Experience supporting the build-out and running of transformation pipeline and monitoring automation deployments.
- Experience developing the robotics and automation discipline with a focus on strategy development, management, and planning as well as program leadership and delivery execution, including leading internal and external resources to deliver on outcomes.
- Experience deploying intelligent automation across all areas of operations and integrating automation with ML/Models.
- Expertise analyzing and designing to support project requests, such as data analysis, business process analysis, software analysis, data model design, program specifications and project request estimates.
- Experience in the direction analysis, definition, and prioritization of business requirements, including creating and administering department project budgets.
- Experience managing the functional goals in the areas of project management, services, system health and performance metrics.
- Experience with O2C, P2P, R2R processes and ability to identify operational areas of automation opportunities.
- DevOps expertise, Management of infrastructure leveraged to develop and deploy ML Models and integrate with Process automation/RPA.
- Data Engineering experience, Working with OpCo’s to get their data ready for modeling (Working in conjunction with Intelligent Automation initiatives).
- Work closely with data scientists, process automation engineers to design and deploy large-scale machine learning and process automation solutions that can handle huge volumes of data with high performance and accuracy which includes data exploration, data preparation, feature engineering, model selection, and process automation.
- Develop and maintain tools for monitoring and analyzing the performance of machine learning models in production.
- Supports life cycle management of deployed Automation & ML models (e.g., retraining, new releases, change management, monitoring, and troubleshooting).
- Collaborate with product managers and process automaton engineers to understand business requirements and translate them into machine learning solutions and integrate with RPA.

**Basic Qualifications**:

- Bachelor's degree or higher in Computer Science, Mathematics, or a related field.
- At least 5 years of experience in Process automation, machine learning engineering, data engineering, Software engineering or a related field.
- Strong understanding and experience with process automation, data engineering, building pipelines, feature engineering and data cleansing using technologies like DBT, Dataiku, UiPath, automation anywhere or like tools.
- Proficiency in one or more programming languages such as Python, Java, or C++.
- Experience with big data technologies, relational DB such as Snowflake / SQL Server / Oracle, Hadoop, Spark, or NoSQL databases.
- Strong knowledge and experience with deploying automations & ML/DS models at scale in cloud environments such as AWS or Azure.
- Extensive