Principal AI-Native Software Engineer

AT&T•Atlanta, GA

3d•$155,400 - $261,100•Onsite

About The Position

AT&T is seeking a Principal AI-Native Software Engineer to turn complex business needs into intelligent, production-ready software. The role combines software engineering, agentic AI, LLM-powered applications, and enterprise automation. The engineer partners directly with business and technical stakeholders to take ideas from concept to production and builds scalable Python services, APIs, agentic workflows, and integrations that enable intelligent automation across AT&T. This is a production engineering role, not simply an AI experimentation role. Solutions should combine emerging AI capabilities with established software engineering practices to be secure, reliable, observable, maintainable, and production-ready. The position is full-time and onsite at a designated work location five days per week. No relocation is offered. The role earns an annual salary of $155,400 to $261,100. Individual starting salary may depend on geography, experience, expertise, and education or training. The position has regular status and a 40-hour workweek.

Requirements

At least 8 years of professional software engineering experience building and delivering production applications or services.
Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, a related technical discipline, or equivalent practical experience.
Strong Python development experience, ideally with FastAPI, Flask, or Django.
Hands-on experience designing and developing REST APIs and backend or microservice architectures.
Experience integrating applications with enterprise platforms, databases, APIs, or distributed systems.
Strong knowledge of SQL and relational databases.
Experience with unit testing, integration testing, automated testing, CI/CD, code review, and refactoring.
Experience with Docker and deployment into cloud or enterprise environments.
Working knowledge of production monitoring using structured logging, metrics, tracing, performance analysis, and incident troubleshooting.
Understanding of secure API development, authentication and authorization, secrets management, least privilege, and audit logging.
Hands-on experience integrating LLMs or Generative AI capabilities into software applications.
Experience with tool or function calling, structured prompting, output validation, RAG, retrieval, or other grounding techniques.
Demonstrated use of AI coding assistants as part of the software development lifecycle.
Ability to move quickly from an ambiguous business problem to a working technical solution.
Strong understanding of AI-native software development and how and where LLMs and agentic workflows provide meaningful value.
Ability to build agentic solutions beyond simple chat interfaces that execute multi-step workflows, use tools, interact with systems, and manage state.
Strong knowledge of software architecture, system design, API design, data modeling, distributed systems, and integration patterns.
Experience designing software for production realities, including security, scalability, resiliency, observability, maintainability, and operational support.
Strong communication skills and ability to explain technical decisions and tradeoffs to engineering and non-technical business partners.
Use of modern AI development tools to accelerate delivery without sacrificing software quality.

Nice To Haves

NoSQL or document database experience.
Hands-on experience with LangGraph or comparable agent orchestration frameworks.
Experience designing multi-agent or multi-step agentic workflows.
Experience with Temporal, Celery, Airflow, or other workflow or orchestration technologies.
Knowledge of event-driven architectures using Kafka, SNS/SQS, Pub/Sub, or comparable technologies.
Experience implementing RAG, embeddings, semantic or vector search, and vector databases in production environments.
Experience with OAuth 2.0, OIDC, API gateways, or service mesh technologies.
Experience developing reusable SDKs, internal developer platforms, AI tool libraries, or reference architectures.
Experience with Angular or another modern JavaScript/TypeScript front-end framework.

Responsibilities

Design and build production-grade AI-enabled applications, backend services, and REST APIs using Python and frameworks such as FastAPI, Flask, or Django.
Create agentic AI workflows using LangGraph or similar frameworks, including tool calling, routing, planning and execution, multi-step workflows, and human-in-the-loop patterns.
Partner with business and technical stakeholders in a collaborative 2-in-a-box model, translating ambiguous business challenges into technical designs and working solutions.
Integrate AI applications securely with enterprise APIs, databases, event streams, service gateways, and other internal platforms.
Design reliable tool and service contracts for AI agents, including schemas, validation, idempotency, retries, rate limits, error handling, and access controls.
Develop evaluation strategies for AI and agentic systems, including success criteria, regression testing, prompt and tool validation, guardrails, and release gates.
Implement RAG, vector search, context engineering, structured outputs, and grounding techniques when appropriate to improve accuracy and usability.
Build end-to-end solutions across backend services, databases, and front-end experiences using technologies such as Angular and other modern web frameworks.
Apply secure-by-design practices, including authentication, authorization, secrets management, least privilege, auditability, input validation, and PII-aware data handling.
Build production observability with logging, metrics, distributed tracing, dashboards, alerting, and incident troubleshooting.
Implement automated testing, CI/CD, Docker-based deployment, and resilient distributed-system patterns including retries, timeouts, circuit breakers, backpressure, and graceful degradation.
Use AI coding assistants throughout the engineering lifecycle for code generation, refactoring, testing, debugging, and documentation while maintaining rigorous engineering standards.

Benefits

Medical, dental, and vision coverage
401(k) plan
Tuition reimbursement program
Paid time off and holidays, including at least 23 vacation days each year and 9 company-designated holidays, based on date of hire
Paid parental leave
Paid caregiver leave
Additional sick leave beyond what state and local law require may be available but is unprotected
Adoption reimbursement
Short-term and long-term disability benefits
Life and accidental death insurance
Supplemental benefit programs, including critical illness, accident hospital indemnity, and group legal
Employee Assistance Programs (EAP)
Employee wellness programs
Employee discounts up to 50% off eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available), and AT&T phone