Integration / DevOps Engineer

United Software Group, Inc.
Dallas, TX, United States
24 days ago

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

.NET Framework Artificial Intelligence Amazon Web Services Application Services Microsoft Azure C Sharp (Programming Language) Cloud Computing Continuous Integration Data Infrastructure Data Systems Data Warehousing DevOps
+31 more
Github Identity and Access Management Python (Programming Language) Key Management Networking Basics Operational Databases Systems Integration Datadog Data Logging Enterprise Software Applications Cloud Platform System Istio Delivery Pipeline Large Language Models Snowflake Grafana Cloudformation AI Platforms Gitlab-ci Kubernetes Bicep Enterprise Integration Data Management Virtual Agents Api Gateway Restful APIs Terraform Webhooks Api Management Docker Jenkins

Job description

Integration / DevOps Engineer who can build the infrastructure, deployment pipelines, and integration fabric that enterprise AI and data systems run on. You will own CI/CD, cloud infrastructure, API integration, and observability across client engagements - ensuring that what the engineering team builds is reliably deployed, monitored, and connected to the enterprise ecosystem. What You’ll Do

  • Design and manage CI/CD pipelines for data, AI, and application services - using GitHub Actions, Jenkins, or equivalent tooling.
  • Build and maintain cloud infrastructure (AWS, Azure, or GCP) using Infrastructure-as-Code (Terraform, CloudFormation, or Bicep).
  • Containerise and orchestrate application workloads: Docker, ECS, EKS, or equivalent Kubernetes-based deployments.
  • Develop and maintain API integrations between AI services, data platforms, and enterprise systems (REST, event-driven, MCP tool servers).
  • Implement observability stacks - logging, metrics, tracing, and alerting - for production data and AI services.
  • Manage environment configuration, secrets management, and security controls appropriate to regulated environments.
  • Collaborate with AI Engineers, Data Engineers, and Full Stack Engineers to support deployment and integration needs across workstreams.
  • Troubleshoot production infrastructure and integration issues and drive root-cause resolution.

What We Work On

  • Deployment pipelines for agentic AI applications and data platform services in regulated financial services environments.
  • Cloud infrastructure and security configuration for Snowflake, AWS Bedrock, and LLM-serving infrastructure.
  • API integration layers connecting enterprise systems (CRM, ERP, data warehouses) to AI agent tool ecosystems., Role Overview As a .NET Engineer, you will play a crucial role in shaping the future of AI systems by leveraging your expertise in .NET and C#. Your contributions will directly i…
  • 1 month ago, Senior Azure Cloud/DevOps Engineer 6 month contract to hire Dallas, TX (Hybrid 2-3 days onsite) ** PLEASE NO THIRD PARTY SUB-VENDORS - DO NOT SEND A RESUME IF YOU ARE REPRESE…
  • 3 days ago +

Requirements

  • 3+ years of DevOps, platform engineering, or integration engineering experience with production cloud systems.
  • Hands-on experience with CI/CD tooling (GitHub Actions, Jenkins, GitLab CI, or equivalent).
  • Strong cloud skills on at least one major platform (AWS, Azure, or GCP) - compute, networking, storage, IAM.
  • Experience with containerisation (Docker) and orchestration (ECS, EKS, or Kubernetes).
  • Proficiency with Infrastructure-as-Code (Terraform preferred) and environment management.
  • Solid understanding of API integration patterns (REST, webhooks, event-driven) and networking fundamentals.
  • Working knowledge of Python - for scripting automation, writing pipeline glue code, and integrating with data and AI services via SDKs and REST APIs., * Experience with API gateway and service mesh tooling (AWS API Gateway, Kong, Istio).
  • Familiarity with ML/LLM serving infrastructure and managed AI services (AWS Bedrock, Azure OpenAI endpoints).
  • Observability tooling experience: OpenTelemetry, Datadog, Grafana, or equivalent.
  • Knowledge of enterprise security standards: SOC 2, ISO 27001, data residency requirements.
  • Relevant certifications: AWS DevOps Professional, GCP Professional DevOps Engineer, or equivalent.
  • Prior experience in financial services or regulated cloud environments.

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