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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Development Engineer III - GenAI - **Company:** GM Financial - **Location:** Irving, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, C Sharp (Programming Language), Cloud Engineering, Data Governance, Distributed Systems, Python (Programming Language), Software Engineering, Microsoft Power Automate, Delivery Pipeline, Multi-Agent Systems, IT Architecture, Model Validation, Generative AI, AI Platforms, Kubernetes, Deployment Automation, Virtual Agents, Microservices - **Published:** August 9, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=0e5736834d2b4baa ## About the Role * Deep expertise in software engineering, including architecture, development, and testing. * Proven experience delivering production Generative AI applications using agentic architectures, RAG, and orchestration frameworks. * Strong proficiency in Python, with additional experience in C# or Java. * Familiarity with LangChain, LlamaIndex, or similar agent and orchestration frameworks. * Experience designing microservices, APIs, automated deployment pipelines, and scalable distributed systems. * Strong communication skills with the ability to explain and justify technical decisions to technical and non-technical audiences. * Ability to craft clear deliverables such as diagrams, architecture documents, and other communication materials.Proactive mindset with strong ownership of engineering tasks and information-management responsibilities. Experience: * 4-6 years of software engineering experience required * Experience leading technical initiatives or mentoring peers through influence * High school diploma or equivalent expirience required * Experience with OpenAI, Azure OpenAI, LangChain, and vendor-specific GenAI implementation patterns preferred * Familiarity with cloud-native AI development preferredProfessional certifications in Generative or Agentic AI preferred Additional Knowledge and Skills Working effectively within an AI enabled environment: * Ability to use AI tools (e.g., Microsoft Copilot) to support daily work * Skills in evaluating AI outputs for accuracy, compliance, and bias * Experience integrating AI into workflows to improve efficiency or insights * Familiarity with AI assisted research, summarization, and content generation * Understanding of responsible AI use, including ethics and data protection * Experience with AI assisted software development or automation * Knowledge of prompting techniques to improve output qualityAwareness of emerging GenAI capabilities and limitations ## Description The Senior AI Engineer is a hands-on technical expert responsible for designing, building, and delivering enterprise-grade Generative AI capabilities. In this role, you will work across agentic systems, multi-agent orchestration, Retrieval-Augmented Generation (RAG) architectures, and modern cloud-based AI platforms. This role requires strong engineering judgment, fluency in modern AI development patterns, and the ability to collaborate effectively with product, architecture, and platform teams to deliver scalable, compliant, and resilient AI solutions., * Design, build, and deliver production-ready Generative AI solutions, including agentic and multi-agent systems, RAG pipelines, orchestration frameworks, APIs, microservices, automated pipelines, and testing, with hands-on contribution in Python, C#, or Java. * Define and standardize AI architecture, patterns, libraries, and development practices, selecting and applying cloud AI solutions aligned with enterprise technology strategy. * Ensure AI solutions are secure, compliant, and responsible by embedding privacy, data governance, auditability, PII protection, risk mitigation, and model evaluation in collaboration with security, legal, compliance, and data governance teams. * Partner with product, architecture, and engineering stakeholders to drive aligned solution direction, predictable delivery, and organization-wide adoption of AI best practices. * Drive innovation and thought leadership through continuous exploration of emerging Generative AI technologies, experimentation, proof-of-concepts, and internal knowledge sharing. * Promote engineering excellence with a production-first mindset focused on resilience, observability, and operational readiness. ## Related Videos - [Microservices: how to get started with Spring Boot and Kubernetes](https://www.wearedevelopers.com/videos/242-microservices-how-to-get-started-with-spring-boot-and-kubernetes) - [The Future of Developer Experience with GenAI: Driving Engineering Excellence](https://www.wearedevelopers.com/videos/1107-the-future-of-developer-experience-with-genai-driving-engineering-excellence) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [This App Reached 10,000 Users in One Week. Here's How.](https://www.wearedevelopers.com/videos/100329-this-app-reached-10-000-users-in-one-week-here-s-how) - [Supercharge your cloud-native applications with Generative AI](https://www.wearedevelopers.com/videos/950-supercharge-your-cloud-native-applications-with-generative-ai) - [Should we build Generative AI into our existing software?](https://www.wearedevelopers.com/videos/1129-should-we-build-generative-ai-into-our-existing-software) ## Related Articles - [Got AI ideas but no money? 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