Top 104 Stack developer java, microservices, angular Jobs in Cincinnati, Oh

Google AI Lead Architect
Deloitte —Cincinnati, OH
- $141,200 - $278,300 a year
- Full-time
- Azure
- Computer Science
- Up to 50% travel
Sr Principal Lead Software Engineer (full-stack)
Northrop Grumman —Cincinnati, OH
- $142,200 - $213,200 a year
- Overtime
- Computer science
- Azure
- Computer Science
- Paid holidays
- Disability insurance
12d
AI Native Software Engineering Manager
Accenture —Cincinnati, OH
- $87,400 - $305,000 a year
- Full-time
- Hybrid work
- Mid-level
- 3 years
- Java
- Paid holidays
- Disability insurance
Cyber Identity - PlainID/PBAC Engineering Manager II
Deloitte —Cincinnati, OH
- $134,500 - $265,100 a year
- Full-time
- Up to 50% travel
- 3 years
- Travel
Forward Deployed Engineer- ServiceNow
Deloitte —Cincinnati, OH
- $134,500 - $265,100 a year
- Full-time
- Azure
- Computer Science
- Up to 50% travel
13d
Backend Modernization Engineer III / US Citizens and GC Candidates Only
Hudson Manpower —Cincinnati, OH
- $50 - $55 an hour
- Full-time
- Software troubleshooting
- 5 years
- Office
- Profit sharing
- Paid training
Quick Apply
Enterprise Solution Architect
ProCorp Systems —Cincinnati, OH
- Azure
- Oracle
- 5 years
Salesforce CTA, Associate Vice President
Deloitte —Cincinnati, OH
- $171,500 - $292,000 a year
- Full-time
- Computer science
- Management
- Computer Science
Cyber Full Stack Manager
Deloitte —Cincinnati, OH
- $134,500 - $265,100 a year
- Full-time
- Computer science
- Azure
- Management
5d
Enterprise Architect
TQL —Cincinnati, OH
- $148,000 - $185,000 a year
- Full-time
- Computer science
- Azure
- Computer Science
- Relocation assistance
- Health insurance
Quick Apply
Cloud Native Senior Developer
Great American Insurance Company —Cincinnati, OH
- Full-time
- Computer science
- Azure
- Computer Science
- Commuter assistance
- Employee stock purchase plan
Quick Apply

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Google AI Lead Architect

Deloitte -
Cincinnati, OH

Apply Now

Job Details

Full-time
$141,200 - $278,300 a year

Qualifications

AI models
Containerization systems
Performance monitoring
DevSecOps Practices
Network design
Software engineering
Azure
Application Architecture Design (Architecture design skill)
Implementing cloud migration projects
Software implementation
Network security implementation
Generative models
Enterprise solutions implementation
Application deployment
AI platforms (beyond public GPTs)
Scalable systems
Enterprise software systems development
Infrastructure architecture design
Machine learning cloud services
AWS
Machine intelligence
Model deployment
Data Security (Data management)
Terraform
Developing large-scale AI models
Scalability
Monitoring system implementation
System deployment
Cloud automation
DevOps automation

Full Job Description

Google AI Lead Architect/AI & Engineering:

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models-traditional teams, pools, or pods-are tailored to each client's needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.

Recruiting for this role ends on 8-31-2026

Work you'll do:

Architect and deliver enterprise AI platforms and applications on Google Cloud using Vertex AI and Gemini; optimize for scalability, reliability, security, and cost.
Design, fine-tune, evaluate, and govern LLM solutions with Gemini on Vertex AI (prompt/tool/function calling, safety policies, Vector Search, evaluation); implement deployment, inference optimization, and monitoring.
Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability.
Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs/microservices, and CI/CD/MLOps/LLMOps with Vertex AI Pipelines and Cloud Build.
Lead cloud-native development on GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL/Spanner, Memorystore, and Terraform; enforce application and agentic design patterns.
Implement security and governance for AI/ML systems (data privacy, model poisoning, adversarial attacks); apply Gemini safety features and enterprise guardrails.

Responsibilities include:

Architect and Design: Lead the design and development of enterprise-grade AI applications and platforms, with a focus on scaling AI solutions for production. This includes defining the technical architecture, selecting appropriate technologies, and ensuring solutions are robust, scalable, and secure.
LLM and AI Integration: Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an emphasis on production-level performance and reliability.
Enterprise Architecture: Collaborate with enterprise architects to ensure AI solutions align with the broader company's technical strategy, governance, and standards.
Cloud and GenAI Native Development: Design and deploy applications using Cloud Native principles on a hyperscaler platform (AWS, Azure, GCP). Leverage a wide range of hyperscaler tools and services, including containers (Docker, Kubernetes), serverless functions, and managed databases. Should have experience in leveraging various GenAI tools to accelerate software development life cycle.
Security & Governance: Ensure the security of all AI/ML systems by addressing potential vulnerabilities such as data privacy concerns, model poisoning, and adversarial attacks.
Design Patterns: Apply and enforce Application Design Patterns and Agentic Design Patterns to build resilient and maintainable software systems.

Required Qualifications

Bachelor's degree in Computer Science, Engineering or a related technical field.
8+ years' experience as a Software or Solution Architect, with a strong focus on application development and scaling solutions for production environments.
5+ years hands-on with Google Cloud, including 2+ end-to-end enterprise implementations in production.
4+ years designing and implementing Google Cloud networks, security controls, and landing zones using Terraform.
3+ years building and operating containerized workloads on GKE (autoscaling, ingress, monitoring/observability).
3+ years implementing CI/CD and DevSecOps with Cloud Build, GitHub Actions, or Jenkins.
3+ years executing migration or modernization programs to Google Cloud (rehost, replatform, refactor).
2+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, including 1+ years' production deployment (e.g. RAG with Vertex AI Search/Vector Search, prompt design, safety policies, observability).
Deep understanding of AI/ML concepts, including experience with LLMs and their application in enterprise settings.
Experience implementing multiple AI solutions in a professional, real-world environment.
Strong understanding of security implications related to AI/ML systems (e.g., data privacy, model poisoning, adversarial attacks).
Familiarity with various hyperscaler tools and services.
Hyperscaler Architect certification is required (e.g., AWS Certified Solutions Architect, Azure Solutions Architect Expert, or GCP Professional Cloud Architect).
Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.

Preferred Qualifications:

Google Professional Machine Learning Engineer certification or the equivalent ML certification.
Master's degree in technology-related discipline.
2+ years's leading high performance, results driven engineering teams delivering AI platforms or applications.
1+ year implementing LLMOps/MLOps using Vertex AI Pipelines and Cloud Build (or similar)

Wages + Salary

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $ 141,200 to $ 278,300 .

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Apply Now

Refine Your Search

stack developer java, microservices, angular jobs in cincinnati, oh

Google AI Lead Architect

Sr Principal Lead Software Engineer (full-stack)

AI Native Software Engineering Manager

Cyber Identity - PlainID/PBAC Engineering Manager II

Forward Deployed Engineer- ServiceNow

Backend Modernization Engineer III / US Citizens and GC Candidates Only

Enterprise Solution Architect

Salesforce CTA, Associate Vice President

Cyber Full Stack Manager

Enterprise Architect

Cloud Native Senior Developer

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