Agentforce AI & Cloud Backend Engineering - Atlanta, GA

Job Description

Job Description

DTS is looking for experienced Agentforce AI & Cloud Backend Engineering for our Client position based in Atlanta, GA

 

 

Job Description:

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.
Basic Qualifications: (What are the skills required to this job with minimum years of experience on each)

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.