Top 12 Vp of engineering Jobs in Suwanee, Ga

VP, Global Engineering and Automation Enablement
Resolution Technologies —Dunwoody, GA
- Azure
- System design
- Continuous improvement
VP of Engineering
Universal Avionics —Duluth, GA
- Full-time
- Engineering
- Master's degree
- Doctor of Philosophy
- Paid holidays
- Relocation assistance
Quick Apply
13d
AVP, Platform Engineering & Operations
Primerica —Duluth, GA
- $185,000 - $195,000 a year
- Full-time
- Computer Science
- Engineering
- Recruiting
- Health savings account
- Disability insurance
Cloud Security Controls Engineering - VP
Morgan Stanley —Alpharetta, GA
- Full-time
- Computer science
- 7 years
- Azure
Cloud & Storage Engineer VP
Morgan Stanley —Alpharetta, GA
- Full-time
- 7 years
- Oracle
- Bachelor's degree
Principal AI App Dev Engineer - Vice President
Morgan Stanley —Alpharetta, GA
- Full-time
- Azure
- System design
- 3 years
7d
Vice President, Lead Software Engineer
Morgan Stanley —Alpharetta, GA
- $197,000 a year
- 5 years
- Research
- Office
7d
Vice President, Mechanical Engineering
WSP —Atlanta, GA
- 5 years
- Engineering
- Office
- Disability insurance
- Health insurance
VP, Staff Cryptography Engineer
Synchrony —Alpharetta, GA
- $135,000 - $230,000 a year
- 18 years or older
- Pass drug screening
- 3 years
- Work from home
Assistant Vice President, Structural Engineer (Buildings)
WSP —Atlanta, GA
- Master's degree
- Analysis skills
- Quality control
- Disability insurance
- Health insurance
Vice President, Electrical Engineer
WSP —Atlanta, GA
- 5 years
- Engineering
- Office
- Disability insurance
- Health insurance
Vice President, Electrical Engineer (Mission Critical/Data Center)
WSP —Atlanta, GA
- 11+ years
- Office
- Analysis skills
- Disability insurance
- Health insurance

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VP, Global Engineering and Automation Enablement

Resolution Technologies -
Dunwoody, GA

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Job Details

Qualifications

AI models
System design
Scalable systems
Microservices
Event-driven architecture
Machine intelligence
Design engineering
Systems engineering
Cloud Native Design
Scalability
Cloud automation
Machine learning (ML) fundamentals
Distributed computing
AI-driven automation
Design (software development lifecycle)
Senior leadership

Full Job Description

VP, Global Engineering and Automation Enablement

***This role is onsite.***

VP, Global Engineering and Automation Enablement Role Overview
We are seeking a senior Technology Leader to own the architecture, scalability, and intelligent automation of our core FinTech platforms. This role is responsible for designing large-scale, cloud-native, distributed systems while leveraging AI-driven automation to improve platform efficiency, reliability, and operational scale.
The ideal candidate combines deep expertise in platform architecture and distributed systems with a strong point of view on using AI to automate infrastructure operations, optimize performance, and enable predictive, self-healing platforms. This is a highly technical leadership role with material influence over how the platform scales as the business grows.
VP, Global Engineering and Automation Enablement Key Responsibilities
Platform Architecture & Technical Strategy

Own the end-to-end platform architecture supporting core FinTech products and transaction flows
Define architectural standards for scalability, performance, resiliency, and system composability
Lead evolution from tightly coupled or monolithic systems toward distributed, service-oriented platforms
Establish clear system boundaries, ownership models, and architectural governance
Define and execute a multi-year platform roadmap aligned with growth, transaction scale, and product velocity

Scalability & Distributed Systems

Design platforms capable of handling high transaction volumes, burst traffic, and sustained throughput
Guide horizontal scaling strategies across compute, storage, data, and messaging layers
Lead architectural decisions around sharding, partitioning, caching, asynchronous processing, and concurrency
Continuously improve latency, throughput, and resource efficiency across the platform
Enable multi-region and multi-environment scalability where required

Cloud & Infrastructure Architecture

Architect cloud platforms (AWS, Azure, or GCP) optimized for scale, availability, and operational efficiency
Define reference architectures for containerized workloads, microservices, and distributed runtimes
Lead Kubernetes and container platform adoption and standardization
Mature Infrastructure as Code (Terraform, CloudFormation, etc.) for consistent, scalable environments
Own capacity modeling, growth forecasting, and infrastructure lifecycle planning

AI-Driven Automation & Intelligent Platforms

Apply AI and machine learning techniques to automate platform operations and decision-making
Use AI for:
- Capacity forecasting and demand prediction
- Anomaly detection in platform performance and system behavior
- Automated root-cause analysis and incident correlation
- Predictive scaling and infrastructure optimization
Drive adoption of self-healing platform patterns where systems can respond automatically to failure or degradation
Enable data pipelines, feature stores, and runtime environments required to support AI-enabled platform services
Partner with data and engineering teams to productionize AI capabilities within core platform workflows

Platform Engineering & Developer Enablement

Build shared platform capabilities that abstract complexity and enable product teams to scale independently
Provide self-service infrastructure, golden paths, and opinionated platform tooling
Standardize CI/CD, runtime environments, observability, and deployment patterns
Reduce friction and cognitive load for application teams through strong platform design
Measure and improve developer experience as a platform outcome

Reliability, Performance & Intelligent Operations

Lead SRE practices focused on scalability, automation, and operational maturity
Define and track SLIs/SLOs centered on throughput, latency, availability, and platform health
Establish advanced observability (metrics, tracing, logging) as inputs to AI-driven insights
Lead analysis of scaling failures, performance bottlenecks, and systemic inefficiencies
Drive continuous improvement toward predictable, automated, and resilient operations

Required Qualifications

10+ years of experience designing and operating large-scale distributed systems
5+ years in senior technical leadership roles (Director, Principal, VP, or equivalent)
Deep expertise in platform architecture, cloud-native design, and system scalability
Strong hands-on experience with AWS, Azure, or GCP
Proven experience with microservices, event-driven architectures, and distributed data systems
Solid background in Infrastructure as Code and automation-first platform design
Experience applying AI/ML concepts to operational or platform use cases

Preferred Qualifications

Experience with high-volume transaction processing or real-time systems
Strong Kubernetes and container platform experience
Experience with event streaming platforms (Kafka or equivalent)
Background modernizing legacy platforms at scale
Experience with AI-assisted operations, AIOps, or intelligent monitoring platforms

Key Competencies

Systems-level architectural thinking with a strong scalability mindset
Ability to blend platform engineering and AI automation into practical solutions
Technical credibility with senior engineers, architects, and leadership
Pragmatic decision-maker who balances ideal architecture with real-world constraints
Strong communicator who can translate technical strategy into business impact

30-60-90 Day Success Plan
First 30 Days – Understand & Assess

Develop deep understanding of current platform architecture and scaling limits
Review system topology, transaction paths, and performance characteristics
Identify opportunities for automation, AI-driven optimization, and architectural simplification
Build strong relationships across engineering, data, and product leadership

Days 31–60 – Architect & Automate

Define target-state platform architecture with explicit scalability patterns
Prioritize architectural improvements with the highest scale and automation leverage
Introduce AI-enabled insights into observability, capacity, or incident analysis
Establish platform standards, reference architectures, and design principles

Days 61–90 – Scale & Industrialize

Deliver measurable improvements in throughput, latency, and platform stability
Advance automation toward self-service, self-scaling, and self-healing capabilities
Roll out platform-level AI automation for operations and performance optimization
Finalize a multi-year platform and AI-automation roadmap
Establish a culture of building intelligent systems designed to scale by default

#RT
#DICEJOBS

teraform,IAC

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Refine Your Search

vp of engineering jobs in suwanee, ga

VP, Global Engineering and Automation Enablement

VP of Engineering

AVP, Platform Engineering & Operations

Cloud Security Controls Engineering - VP

Cloud & Storage Engineer VP

Principal AI App Dev Engineer - Vice President

Vice President, Lead Software Engineer

Vice President, Mechanical Engineering

VP, Staff Cryptography Engineer

Assistant Vice President, Structural Engineer (Buildings)

Vice President, Electrical Engineer

Vice President, Electrical Engineer (Mission Critical/Data Center)

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