Be part of the digital revolution
At Leaniar, we take pride in prioritizing human happiness, our team strive to work on the end goal of liberating humans from robotic work that involves tedious manual and repetitive activities, and create a sustainable path to the future of work.
Leaniar employees are offered opportunities to become certified in cutting-edge technologies that will allow them to build a robust career in a diverse field of job functions. They will also be able to work in our state-side or nearshore offices as well as at our client offices, where they will have the opportunity to grow their professional careers by expanding their skill-set and experience, and collaborating with professionals of diverse cultural backgrounds.
CURRENT JOB OPENINGS:
RPA Lead Developer
The RPA Lead Developer is responsible for leading the delivery of automation solutions to our clients. You will lead a team of developers and analyze and automate various processes using new, cutting-edge technologies that Leaniar is currently implementing, and which are growing very fast on a global scale.
Main responsibilities include the design, implementation, build, test and deployment of Robotics Process Automation (RPA) software such as UiPath, Blue Prism, Automation Anywhere. Development tasks include estimation, analysis, configuration, debugging, troubleshooting, documentation and application health monitoring for RPA implementation and development projects.
UiPath Advanced Developer certification is required.
Minimum 3+ years experience building RPA.
The RPA Developer is responsible for participating in the delivery of automation solutions to our clients. You will analyze and automate various processes using new, cutting-edge technologies that Leaniar is currently implementing, and which are growing very fast on a global scale.
UiPath certification heavily encouraged with 2+ years developing and deploying RPA.
RPA Program Manager
The RPA Program Manager is the face of the RPA program with respects to the client, they are responsible for managing and reporting the overall health of the RPA program to both the client and Leaniar.
Main responsibilities include design and implementation of automation solutions which include Process Analysis; RPA Proof-of-Concept; RPA Pilot Implementation; large scale deployment of RPA across multiple functions; set up of Automation/RPA Center of Excellence and definition of corresponding governance, control, and operating models.
Business Development Representative
The Business Development Representative will focus on prospecting for new clients and business opportunities, as well as qualify leads from marketing campaigns as sales opportunities. They will create a strategic plan to develop the pipeline of new business coming into the company, with a thorough knowledge of the market, the solutions/services Leaniar can provide. They will work closely with marketing and pre-sales staff.
RPA QA Analyst
The Quality Assurance Analyst is responsible for supporting the planning, design, and execution of system testing on simple to complex implementations as well as leading the Change in the company. The QA Analyst works collaboratively within the IT department and business units to execute and validate test cases based upon system requirements.
RPA Infrastructure Engineer
The RPA Infrastructure Engineer is responsible for working with client, Leaniar, and partner resources to identify client environment variables to be used for an RPA infrastructure installation, deploy all software modules for the client’s appropriate RPA platform solution and configure the platform for the client’s RPA needs. This includes all stages, test, development, and production environments in the cloud or on-premise.
Apply at Leaniar
What is Hyperautomation? Gartner calls it “Hyperautomation”, Forrester calls it “Digital Process Automation” and IDC calls it “Intelligent Process Automation”. Hyperautomation brings together several components that traditionally were separate and siloed including process and task mining, enterprise process automation, citizen development, AI/ML, compliance and governance, test automation and insights/dashboarding. Orchestrating these components within one framework or platform accelerates data integration and real-time insights. Those insights can then be used to cultivate the pipeline of further automations.
Leaniar's extensive experience with all Hyperautomation technologies helps organizations accelerate the following goals:
- Enable the modern workforce
- Transform through Business and IT Alignment
- Leverage AI to enable end-to-end automation
- Provide important insight into ROI from automation
For more information on specific Hyperautomation components please review the different sections below and knowledge article links within each section.
What is Robotic Process Automation?
Robotic Process Automation is the technology that allows anyone today to configure computer software, or a “robot” to emulate and integrate the actions of a human interacting within digital systems to execute a business process. RPA robots utilize the user interface to capture data and manipulate applications just like humans do. They interpret, trigger responses and communicate with other systems in order to perform on a vast variety of repetitive tasks. Only substantially better: an RPA software robot never sleeps and makes zero mistakes.
How is Leaniar RPA different from other enterprise automation tools?
In contrast to other, traditional IT solutions, Leaniar RPA allows organizations to automate at a fraction of the cost and time previously encountered. Leaniar RPA is also non-intrusive in nature and leverages the existing infrastructure without causing disruption to underlying systems, which would be difficult and costly to replace. With Leaniar RPA, cost efficiency and compliance are no longer an operating cost but a byproduct of the automation.
- Fast benefit realization
- Minimal upfront investment
- No disruption to underlying systems
- Led by the business, with support from IT
- Highly scalable, adapts to changing business environment
RPA vs. Traditional Automation
Artificial intelligence is a foundational catalyst for advanced process automation and human augmentation and engagement. Artificial intelligence capabilities such as machine learning (ML), natural language processing (NLP), intelligent optical character recognition (OCR), and AI computer vision can now be included with RPA so that robots can read, see, and process more 'cognitive' work.
At Leaniar, we focus on the fusion between Artificial Intelligence and Robotic Process Automation (RPA) as this has been both a challenge and turning point for companies looking to add cognitive capabilities for more complex, multi-variance process automations. While RPA streamlines rules-based business processes, ML algorithms have an extraordinary capacity to automate decision making based on intuition. By integrating custom-built Machine & Deep Learning models with the RPA platform, businesses can achieve the best of both worlds.
The Difference Between Robotic Process Automation and Artificial Intelligence
Process discovery is mainly concerned with the identification of process models from process execution logs. The process log is an audit trail that contains a sequence of events that describe the activities that were carried out in order to complete a certain business process. In general, process discovery algorithms aim to find a process model that best describes the given process log. Process mining techniques can be used for various process discovery tasks, such as identifying the start and end points of a process, finding out how often a certain task is executed, or discovering which resources are used in a process. By applying process mining techniques, organizations can get a better understanding of their business processes and identify potential areas for improvement. Put another way, value of process mining is its ability to see through the noise. To put it another way, imagine your company as a human body. Like the human body, a company is a complex system of elements that need to function together to remain 'healthy.'
Leaniar Process mining is a cutting-edge part of BPM and focuses on gathering enterprise data (referred to as event logs) from corporate IT systems for further analysis. Based on event logs, process mining software extracts existing data about what happened in a process and when. Then, the software algorithms translate the data into comprehensive language and turn logs into a visual workflow. This is what you can analyze! Looking at the actual end-to-end process you can spot any deviation or bottleneck.
Leaniar Process mining is like an x-ray for your organization. You can use it to detect and diagnose any irregularities in your processes. It allows you not only to see where the problem is but also to understand its cause. You can even track how the problem influences other 'organs' and how to prevent its recurrence.
Crowdsourcing Process Automation
Crowdsourcing task automation is a collaborative approach to identifying task automation candidates, estimating ROI and managing pipeline via a task repository tool. The goal is to accelerate the adoption of RPA across your organization, create awareness of automation opportunities and improve automation change management.
This puts business process experts and citizen developers in the driver seat of automation initiatives.
- Task Identification - Submit your own ideas/requests for automation through a collaborative task repository tool (e.g. UiPath Automation Hub)
- Pipeline Management - Your company’s automation plans, their status, expected benefits/ROI, and other important details are displayed in one single place. Users can review the pipeline and provide inputs by voting on the ideas/requests.
- Process & Documentation Bank - A central repository containing all the key documents related to a process selected as a candidate for automation.
- Integration with Task Capture tools - Task Capture tools record the user executing the task steps. This recording can then be used to create the Process Design Document (PDD). The recording output identify the current state of the task and the user will then need to update the PDD with more task details (i.e. inputs, task exceptions, future state flow, automation benefits, etc.) before the automaton can begin.
Advanced Analytics and Insights
At LEANIAR, we focus on RPA analytics solution that tracks, measures, and forecasts the performance of your entire automation program—so you can propel your automation journey to the next level.
Advanced analytics to measure and demonstrate the ROI of automation and its impact based on business outcomes that matter to your company.
Business Process Re-Engineering (BPR)
Lean is the process of organizational transformation with the goal of process efficiency. The lean transformation journey at Leaniar will help organizations to identify, eliminate or optimize wasteful activities. Our goal is to enable business process teams to find ways to deliver more value to customers faster and to practice continuous process improvement as part of daily work.
Key elements of Lean Transformation Framework are as follows:
⦁ Situational Approach - What is the Purpose of the Change?
⦁ Process Improvement – How are we improving the work?
⦁ Capability Development – How are we building capability?
⦁ Management System – What leadership behavior and management systems are required?
⦁ Basic Thinking, Mindset, Assumptions – What basic mindset and cultural change required?
Six Sigma Process Improvement
The process improvement journey contains analytics at its core and Six Sigma as a measurement-based strategy for organizational transformation. Leaniar's Six Sigma certified team will focus on a set of practices designed to identify, analyze and remedy causes of defect within a process or product. Our Lean Six Sigma initiative will leverage the best of both approaches to solve problems of a company by identifying the issues, thinking of an efficient way of solving them and increasing quality of service by reducing variability.
Philosophy: The philosophical perspective of Six Sigma views all work as processes that can be defined, measured, analyzed, improved, and controlled. Processes require inputs (x) and produce outputs (y). If you control the inputs, you will control the outputs. This is generally expressed as y = f(x).
Target Operating Model
A Target Operating Model (TOM) is the desired state of operations, which enables the application of a corporate strategy or vision to a business or operation. At leaniar, we believe that the TOM is the bridge between design and execution. Our TOM design will create a blueprint showcasing how to deliver strategy and how people, processes and technology integrate to support the intended customer journeys.
The Operating Model is HOW a business functions, including WHAT capabilities – the processes, data, people and systems it required to keep itself running – which need to be applied at the right time (WHEN) and in the right place, in different locations (WHERE). TOM is a high-level representation of how a company can best be organized to more efficiently & effectively deliver and execute on the organization’s strategy. It provides a common understanding of the organization by allowing people to visualize the organization from a variety of perspectives across the value chain.
The procedure is divided into six categories:
- Optimization: Size, shape, structure and performance of the company can be optimized by the TOM
- Preparation for transformation: Identification of gaps between the current and target state of the company and the determination of dependencies and impact of the change
- Consolidation: Different business areas or divisions should be brought together. This ensures the alignment of key components (people, culture, technology, processes, etc.)
- Strategic planner: The operational implementation of the new business strategy requires clear communication of the principles and objectives
- Consensus building: The TOM should include a concrete set of structural views
- Cost reduction: Identification of cost reduction potential and company-related inefficiencies