DevOps Platform Engineer

DevOps Platform Engineer with our client in the financial industry located in Charlotte, NC and New York, NY. This is a 12 + month contract position.

Responsibilities

• Collaborate with team and with partners in QSDG and Platform to define, build, test, and deploy platform meeting requirements

• Define & enforce standards & best practices related to platform management

• Evaluate third-party products to meet scalability, resiliency, and performance

• Build new or leverage existing platforms (Lab, SDLC) by automating setup, installation, verification, monitoring & provisioning processes

• Maintain a central, version controlled, inventory of all environments, including their current versions and configuration settings

• Plan & allocate environments to teams depending on their delivery lifecycle

• Analyze data to identify and proactively address environment-related issues

• Work with project teams to manage costs & improve efficiency of environments

• Partner closely with Prod Support and Engineering to deploy & support applications

Requirements

• 7-10 years in similar roles; preferably in the financial industry

• Higher education in IT field or relevant previous work experience

• Prior experience designing, implementing, and maintaining end to end environments, from POC to production

• Deep understanding of hardware, software, network, data & application configuration

• DevOps processes and CICD tooling (Jira, Git/Bitbucket, Jenkins, Datival, Artifactory, Ansible), orchestration & automation

• Multi-tier (Python based) web application stack microservices/serverless/loosely coupled architecture

• Mix of on-premises and cloud based, containerized (Docker/Kubernetes/OpenShift) deployment models

• Familiarity with no-SQL (MongoDB) and relational (SQL Server/Oracle) databases, and other various forms of Object, Vector, and file stores

• Unix scripting, SQL, work scheduling tools

• Setting up infrastructure monitoring & reporting for GPU/CPU & memory consumption, inference latency and model performance

• Performance profiling & optimization techniques to maximize performance & resource consumption / throughput and minimize latency

• Load balancing, high availability & backup recovery strategies/techniques

• Ability to communicate effectively to a wide range of audience (business stakeholders, developer & support teams)

• Meticulous & highly organized

• Adaptable to shifting & competing priorities

• Skilled at delegating, mentoring & setting expectations

• Critical thinking skills to diagnose & resolve complex issues

• Desired skills:

• Familiarity with AI & Deep learning, modeling techniques, Generative AI application stack

• Proficiency in Python and familiarity with AI frameworks (TensorFlow/PyTorch)

• GPU cluster management (CUDA/Kubernetes), auto-scaling & scheduling (Triton Inference Server)