Principal Software Engineer/Developer

Position Description: 

Develops highly scalable and distributed systems in Cloud technologies (AWS and Lambda). Supports mission critical applications using Object Oriented Programming -- Java, Scala, or Python. Resolves technical roadblocks for the team and mitigates potential risks using Relational and NoSQL databases (PostgreSQL and DynamoDB) and data movement technologies (Extract Transform Load/Extract Load Transform (ETL/ELT). Delivers system automation by setting up Continuous Integration/Continuous Delivery (CI/CD) pipelines using DevOps technologies (Maven, Git, Jenkins, Stash, or Docker). Develops and oversees software system testing and validation procedures, programming, and documentation. Uses business knowledge to translate the vision for divisional initiatives into business solutions by developing complex or multiple software applications and conducting studies of alternatives. Analyzes and recommends changes in project development policies, procedures, standards, and strategies to development experts and management. 

Primary Responsibilities: 

• Participates in architecture design teams. 

• Defines and implements application-level architecture. 

• Develops applications on complex projects, components, and subsystems for the division. 

• Recommends development testing tools and methodologies and reviews and validates test plans. 

• Responsible for QA readiness of software deliverables. 

• Develops comprehensive documentation for multiple applications or subsystems. 

• Establishes full project life cycle plans for complex projects across multiple platforms. 

• Responsible for meeting project goals on-time and on-budget. 

• Advises on risk assessment and risk management strategies for projects. 

• Plans and coordinates project schedules and assignments for multiple projects. 

• Acts as a primary liaison for business units to resolve various project/technology issues. 

• Provides technology solutions to daily issues and technical evaluation estimates on technology initiatives. 

• Advises senior management on technical strategy. 

• Mentors junior team members. 

• Performs independent and complex technical and functional analysis for multiple projects supporting several divisional initiatives.  

• Develops original and creative technical solutions to on-going development efforts. 

Education and Experience: 

Bachelor’s degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and five (5) years of experience as a Principal Software Engineer/Developer (or closely related occupation) developing Machine Learning (ML) platform applications for Cloud infrastructures (Amazon Web Services (AWS), Azure, Google, or IBM) using Agile Methodologies.  

Or, alternatively, Master’s degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and three (3) years of experience as a Principal Software Engineer/Developer (or related occupation) developing Machine Learning (ML) platform applications for Cloud infrastructures (Amazon Web Services (AWS), Azure, Google, or IBM) using Agile Methodologies. 

Skills and Knowledge: 

Candidate must also possess: 

• Demonstrated Expertise (“DE”) designing, building, and applying auto-ML infrastructure and tools to develop, deploy, monitor, and interpret ML models using AWS SageMaker, Google Colab, Azure Cloud, or Anaconda; and building tools to detect data drifts that impact prediction quality and model monitoring, interpretability, and explainability using Python’s ML and Deep Learning (DL) ecosystem (numpy, pandas, sklearn, tensorflow, or keras). 

• DE designing and developing scalable and secure applications using Cloud technologies according to standard security practices and distributed architectural requirements – Identity and Access Management (IAM), fine-grain access controls, and encryption schemes using infrastructure as a code. 

• DE achieving auto-scale analysis for users and use cases within an organization environment using Kubernetes and Open-Source Software (EKS); accelerating data exploration and model development using notebook interfaces and tools (Spark Technology); applying version control (Git) while developing AI solutions in Agile methodologies; and deploying data science infrastructure using CI/CD and orchestration tools (AWS Step Functions and MLflow). 

• DE analyzing Big Data applications; designing and developing batch processing jobs that perform ETL to support predictive analytics using AWS Glue, SSIS, or Spark; building and troubleshooting high performance big data applications using multi-threading, multi-processing, asynchronous programming using distributed computing architecture and programming languages (Python and Java).