What are the responsibilities and job description for the Agentforce AI & Cloud Backend Engineering - Atlanta, GA position at Digital Technology Solutions?
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.
Nice to Have (But Not Required)
- 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.
DTS offers excellent compensation package.
Contact:
Ajay Bharbutta
Digital Technology Solutions