Software Engineer - AI Integration & Data Platforms
AT&T
Software Engineer - AI Integration & Data Platforms
Job Description
Overall Purpose:Design, develop, and maintain software solutions that enable AI-powered workflows, enterprise application integration, and secure automation. Build scalable APIs, Model Context Protocol (MCP) servers, Python-based services, and cloud-native components that connect business systems, data platforms, and AI agents. Partner with engineering, product, and business stakeholders to deliver reliable, secure, and maintainable solutions using modern DevOps practices, Azure DevOps, CI/CD pipelines, automated testing, and strong software engineering standards.Key Roles and Responsibilities:Typical tasks may include, but are not limited to, the following:AI-Enabled Software Development: Design, build, and maintain software capabilities that support AI-enabled workflows, including MCP servers, agent-facing tools, and application integrations that allow enterprise systems and data sources to be accessed securely and consistently.API and Service Development: Develop robust APIs, backend services, and integration layers using Python and modern service patterns, with emphasis on reliability, maintainability, authentication, observability, and clear interface design.MCP Server and Tooling Implementation: Implement MCP tools and server-side capabilities that expose business functions, data access patterns, and automation workflows to AI agents while enforcing security, access controls, and responsible usage guardrails.DevOps and CI/CD Automation: Build, enhance, and maintain CI/CD pipelines in Azure DevOps or similar platforms, supporting automated builds, testing, code quality checks, artifact management, deployments, and repeatable release processes.Cloud-Native Engineering: Develop and deploy cloud-ready services using Azure-based patterns, containerized workloads, secure configuration management, logging, monitoring, and scalable runtime architectures.Collaboration and Documentation: Partner with product owners, software engineers, data engineers, security teams, and business stakeholders to translate requirements into durable technical solutions. Document APIs, MCP tools, deployment patterns, runbooks, and engineering standards for long-term support and reuse.Job Contribution:Independently design, develop, and support AI-enabled software solutions, APIs, MCP servers, and cloud-native services using strong DevOps practices. Lead moderate-sized technical efforts, contribute to architecture decisions, improve engineering standards, and deliver secure, scalable solutions that accelerate automation, AI adoption, and business productivity.What You’ll Need (Required Skills):Hands-on experience with:Python development for applications, services, automation, or integration workProficiency with general software engineering languages and practices, with the ability to work across modern programming stacks as neededAPI development using modern backend frameworks and secure service design patternsMCP server or AI tool development, including exposing structured tools, data access, or workflow automation to AI agentsAzure DevOps, Git-based development workflows, CI/CD pipelines, automated testing, and release automationStrong understanding of software engineering fundamentals, including code quality, modular design, version control, security, logging, monitoring, and documentation best practices.Experience collaborating across engineering, data, AI, security, and business teams to gather requirements and deliver reliable enterprise software solutions.Preferred Qualifications:Experience with FastAPI, FastMCP, SQLAlchemy, containerized deployments, or cloud-hosted Python servicesFamiliarity with Azure services, managed identity, Key Vault, container platforms (Docker), private networking, or enterprise authentication patternsExperience with AI-assisted development tools, prompt-aware engineering workflows, agentic architectures, or LLM application integrationHands-on experience with LangGraph and LangChain for developing LLM-powered applications, agents, and workflow orchestrationContractual name of the role: Senior Specialist Software EngineeringLocation: Bratislava, SlovakiaWorking hours: EMEASalary: The gross monthly base salary for this position ranges from EUR 3,200 to EUR 4,900. The final offer will reflect your skills, experience, and overall qualifications. In addition to a competitive compensation package, we offer a variety of other attractive benefits.Weekly Hours:40Time Type:RegularLocation:Bratislava, SlovakiaAT&T and its subsidiaries are committed to equal employment opportunity. All hiring, promotion, and other employment decisions remain merit-based and free from discrimination on the basis of race, color, religion, religious creed, national origin, ancestry, age, sex, sexual orientation, gender, gender identity, gender expression, physical disability, mental disability, pregnancy, medical condition, genetic information, marital status, citizenship status, military status, veteran status, or any other characteristic protected by federal, state, or local laws. In addition, AT&T will provide reasonable accommodations to qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made. Click here to learn more or request an application accommodation here.
Locations
- Slovakia, Bratislava
Skills Required
- general software engineering languagesintermediate
- FastAPIintermediate
- Azure servicesintermediate
- AI-assisted development toolsintermediate
- LangGraphintermediate
Required Qualifications
- Hands-on experience with: (experience)
- Python development for applications, services, automation, or integration work (experience)
- Proficiency with general software engineering languages and practices, with the ability to work across modern programming stacks as needed (experience)
- API development using modern backend frameworks and secure service design patterns (experience)
- MCP server or AI tool development, including exposing structured tools, data access, or workflow automation to AI agents (experience)
- Azure DevOps, Git-based development workflows, CI/CD pipelines, automated testing, and release automation (experience)
- Strong understanding of software engineering fundamentals, including code quality, modular design, version control, security, logging, monitoring, and documentation best practices. (experience)
- Experience collaborating across engineering, data, AI, security, and business teams to gather requirements and deliver reliable enterprise software solutions. (experience)
- Python development for applications, services, automation, or integration work (experience)
- Proficiency with general software engineering languages and practices, with the ability to work across modern programming stacks as needed (experience)
- API development using modern backend frameworks and secure service design patterns (experience)
- MCP server or AI tool development, including exposing structured tools, data access, or workflow automation to AI agents (experience)
- Azure DevOps, Git-based development workflows, CI/CD pipelines, automated testing, and release automation (experience)
- Strong understanding of software engineering fundamentals, including code quality, modular design, version control, security, logging, monitoring, and documentation best practices. (experience)
- Experience collaborating across engineering, data, AI, security, and business teams to gather requirements and deliver reliable enterprise software solutions. (experience)
Preferred Qualifications
- Experience with FastAPI, FastMCP, SQLAlchemy, containerized deployments, or cloud-hosted Python services (experience)
- Familiarity with Azure services, managed identity, Key Vault, container platforms (Docker), private networking, or enterprise authentication patterns (experience)
- Experience with AI-assisted development tools, prompt-aware engineering workflows, agentic architectures, or LLM application integration (experience)
- Hands-on experience with LangGraph and LangChain for developing LLM-powered applications, agents, and workflow orchestration (experience)
- Experience with FastAPI, FastMCP, SQLAlchemy, containerized deployments, or cloud-hosted Python services (experience)
- Familiarity with Azure services, managed identity, Key Vault, container platforms (Docker), private networking, or enterprise authentication patterns (experience)
- Experience with AI-assisted development tools, prompt-aware engineering workflows, agentic architectures, or LLM application integration (experience)
- Hands-on experience with LangGraph and LangChain for developing LLM-powered applications, agents, and workflow orchestration (experience)
- Contractual name of the role: Senior Specialist Software Engineering (experience)
- Location: Bratislava, Slovakia (experience)
- Working hours: EMEA (experience)
- Salary: The gross monthly base salary for this position ranges from EUR 3,200 to EUR 4,900. The final offer will reflect your skills, experience, and overall qualifications. In addition to a competitive compensation package, we offer a variety of other attractive benefits. (experience)
Responsibilities
- Typical tasks may include, but are not limited to, the following:
- AI-Enabled Software Development: Design, build, and maintain software capabilities that support AI-enabled workflows, including MCP servers, agent-facing tools, and application integrations that allow enterprise systems and data sources to be accessed securely and consistently.
- API and Service Development: Develop robust APIs, backend services, and integration layers using Python and modern service patterns, with emphasis on reliability, maintainability, authentication, observability, and clear interface design.
- MCP Server and Tooling Implementation: Implement MCP tools and server-side capabilities that expose business functions, data access patterns, and automation workflows to AI agents while enforcing security, access controls, and responsible usage guardrails.
- DevOps and CI/CD Automation: Build, enhance, and maintain CI/CD pipelines in Azure DevOps or similar platforms, supporting automated builds, testing, code quality checks, artifact management, deployments, and repeatable release processes.
- Cloud-Native Engineering: Develop and deploy cloud-ready services using Azure-based patterns, containerized workloads, secure configuration management, logging, monitoring, and scalable runtime architectures.
- Collaboration and Documentation: Partner with product owners, software engineers, data engineers, security teams, and business stakeholders to translate requirements into durable technical solutions. Document APIs, MCP tools, deployment patterns, runbooks, and engineering standards for long-term support and reuse.
- AI-Enabled Software Development: Design, build, and maintain software capabilities that support AI-enabled workflows, including MCP servers, agent-facing tools, and application integrations that allow enterprise systems and data sources to be accessed securely and consistently.
- API and Service Development: Develop robust APIs, backend services, and integration layers using Python and modern service patterns, with emphasis on reliability, maintainability, authentication, observability, and clear interface design.
- MCP Server and Tooling Implementation: Implement MCP tools and server-side capabilities that expose business functions, data access patterns, and automation workflows to AI agents while enforcing security, access controls, and responsible usage guardrails.
- DevOps and CI/CD Automation: Build, enhance, and maintain CI/CD pipelines in Azure DevOps or similar platforms, supporting automated builds, testing, code quality checks, artifact management, deployments, and repeatable release processes.
- Cloud-Native Engineering: Develop and deploy cloud-ready services using Azure-based patterns, containerized workloads, secure configuration management, logging, monitoring, and scalable runtime architectures.
- Collaboration and Documentation: Partner with product owners, software engineers, data engineers, security teams, and business stakeholders to translate requirements into durable technical solutions. Document APIs, MCP tools, deployment patterns, runbooks, and engineering standards for long-term support and reuse.
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