> Markdown version of [/jobs/ext/2425221-backend-ai-consulting](https://www.wearedevelopers.com/jobs/ext/2425221-backend-ai-consulting). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Backend AI Consulting - **Company:** Technogen, Inc. - **Location:** Alpharetta, GA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, BigQuery, Cloud Computing, Cloud Engineering, Cloud Storage, Code Review, Information Engineering, Identity and Access Management, Python (Programming Language), Machine Learning, Natural Language Processing, Release Management, Tensorflow, Salesforce.Com, Software Engineering, Data Streaming, Systems Integration, Google Cloud, Enterprise Software Applications, Software Application Programming, Generative AI, Backend, Event Driven Architecture, AI Platforms, Kubernetes, Information Technology, Deployment Automation, Google Cloud Functions, Apache Kafka, Machine Learning Operations, Api Gateway, Restful APIs, Terraform, Data Pipelines, Serverless Computing, Databricks, Artifactory, Microservices - **Published:** August 31, 2026 - **Apply:** https://www.dice.com/job-detail/0a73ff00-95b8-4773-b278-a2e5d66bd3aa ## About the Role * Minimum 3 5 years of experience in Backend Engineering, AI/ML Engineering, Cloud Engineering, or Software Development. * Minimum 3 years of hands-on experience developing applications using Python. * Minimum 2+ years of experience designing and deploying solutions on Google Cloud Platform, including Cloud Run, GKE, BigQuery, Cloud Storage, AlloyDB, and serverless services. * Minimum 2 years of experience developing RESTful APIs and integrating enterprise applications using Google Cloud API Gateway. * Minimum 2 years of experience implementing AI/ML or data engineering solutions using Databricks. * Experience implementing Infrastructure as Code using Terraform. * Experience building CI/CD pipelines utilizing GitOps methodologies, Azure DevOps, and JFrog Artifactory. * Experience working with messaging and event streaming technologies such as Google Pub/Sub and Kafka. * Strong understanding of Google Cloud Platform IAM, cloud networking, encryption, security, and governance best practices. * Excellent analytical, troubleshooting, communication, and stakeholder collaboration skills. Travel: This position may require up to 20 30% travel depending on client engagements, project requirements, and business needs. Degree: Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent work experience. Nice to Have: * Experience with Salesforce Agentforce or enterprise AI platforms. * Experience working with Google's Gemini models or other Generative AI technologies. * Knowledge of MLOps frameworks and model lifecycle management. * Experience with Kubernetes and container orchestration. * Consulting or client-facing implementation experience. * Technical leadership or project coordination experience ## Description At Client, we know that with the right people on board, anything is possible. The quality, integrity, and commitment of our employees are key factors in our company's growth, market presence and our ability to help our clients stay a step ahead of the competition. By hiring the best people and helping them grow both professionally and personally, we ensure a bright future for client and for the people who work here., * Design, develop, and implement scalable AI-powered backend solutions supporting enterprise Agentforce initiatives on Google Cloud Platform. * Develop intelligent applications leveraging Google's Gemini API and modern AI/ML frameworks for natural language processing, automation, and generative AI use cases. * Architect, develop, and optimize cloud-native microservices using Python, Cloud Run, and serverless technologies to deliver secure, highly available, and scalable solutions. * Build and enhance RESTful APIs utilizing Google Cloud API Gateway while ensuring security, governance, and performance best practices. * Develop and maintain AI/ML data processing pipelines using Databricks to support model training, inference, and enterprise analytics. * Implement Infrastructure as Code (IaC) using Terraform and automate deployments through GitOps-based CI/CD pipelines using Azure DevOps. * Manage build artifacts, package repositories, and release management utilizing JFrog Artifactory. * Design and implement event-driven architectures using Google Pub/Sub and Kafka to enable scalable enterprise integrations. * Work closely with Product Owners, Data Engineering, Infrastructure, and Architecture teams to deliver business-driven AI solutions. * Ensure solutions adhere to Google Cloud security standards including IAM, encryption, networking, compliance, and operational excellence. * Participate in technical solution design, architecture discussions, code reviews, and client workshops while providing technical guidance and implementation best practices. * Support client engagements by contributing to technical estimations, solution design, and implementation planning for AI and cloud transformation initiatives. ## Related Videos - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Implementing Feature Environments with AWS and Terraform](https://www.wearedevelopers.com/videos/531-implementing-feature-environments-with-aws-and-terraform) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers)