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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Developer (Emerging Careers) - **Company:** Sas Institute Inc. - **Location:** Cary, NC, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, JIRA, Microsoft Azure, Software Code Optimization, Code Review, Continuous Integration, Document-Oriented Databases, Github, Python (Programming Language), Object-Oriented Software Development, Parsing, PRINCE2, Scrum Methodology, Cloud Services, SAS (Software), Software Engineering, Google Cloud, Cloud Platform System, Retrieval-Augmented Generation, Large Language Models, NeMo Guardrails, Generative AI, Agentic-AI, Git, AI Platforms, Git Flow, Kubernetes, Information Technology, Deployment Automation, RAGAS (Retrieval Augmented Generation Assessment), Machine Learning Operations, Asynchronous Programming, Model Context Protocol, Software Version Control, Docker, Jenkins - **Published:** October 1, 2026 - **Apply:** https://careers-sas.icims.com/jobs/42297/software-developer-(emerging-careers)/job?mode=apply&apply=yes&in_iframe=1&hub=9&hashed=-336115570 ## About the Role * Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field * Minimum 2 years of experience in software development * Production-level Python development experience with a deep understanding of object-oriented design patterns, memory optimization, and asynchronous programming. * Hands-on experience building complex, stateful applications using LangChain or similar orchestrators. * Hands-on experience developing and integrating Model Context Protocol (MCP) servers and clients to expose tools, data sources, and APIs for consumption by LLM-driven agents in production environments. * Experience deploying LLM-as-a-judge or empirical evaluation tooling (e.g., Ragas, TruLens, MLflow) to bench and score generative outputs. * Practical experience creating, deploying, and managing containerized cloud workloads using Docker or Kubernetes. * Proficiency with version control (git, GitHub workflows, branching strategies, and rigorous code reviews). * Equivalent combination of related education, training and experience may be considered in place of the above qualifications. Additional competencies, knowledge and skills * Adaptability: Approaches architectural shifts and evolving GenAI trends with a growth mindset, treating rapid technological changes as opportunities for innovation. * Collaborating: Actively seeks input from cross-functional teams, leveraging collective engineering strengths to solve complex data and orchestration challenges. * Communication: Translates complex AI concepts and metric evaluation data into clear, actionable technical insights for both technical stakeholders and product management. * Quality Orientation: Demonstrates a vigilant commitment to minimizing hallucination, optimization bottlenecks, and security vulnerabilities in production GenAI deployments. * Experience working directly with vector databases, embeddings, and complex document parsing methodologies. * Experience with cloud computing platforms such as Azure, AWS, or Google Cloud, and ideally their AI services e.g. Azure Open AI. * Experience implementing safety, alignment, or content-filtering layers (e.g., NeMo Guardrails, Guardrails AI) within LLM pipelines. * Experience with CI/CD deployment automation tools like GitHub Actions or Jenkins. * Exposure to project management frameworks and tracking tools like Jira for task tracking, sprint planning and collaboration. ## Description The Platform Products division is looking for a Software Developer (Emerging Careers) specialized in Generative AI to join the engineering team driving SAS Retrieval Agent Manager. In this role, you will help build and scale cutting-edge, enterprise-grade Retrieval-Augmented Generation (RAG) and autonomous agent architectures. You will play a pivotal role in integrating SAS VIYA agentic technologies with vectorized customer document data, ensuring our LLM-driven solutions are secure, high-performing, and highly scalable. This is an opportunity to directly shape how enterprise customers deploy GenAI at scale by engineering the production-grade infrastructure and guardrails that let sophisticated agentic systems run reliably and respond accurately in mission critical environments. As a Software Developer (Emerging Careers), you will: * Collaborate on the ingestion, processing, and management of vectorized customer document data to optimize retrieval accuracy, latency, and agentic integrations. * Maintain accountability for the entire lifecycle of the code, from translation of product requirements into actionable features, to rigorous testing (functional, unit, and performance), code reviews, and post-deployment support. * Design, develop, and maintain autonomous agent architectures and RAG pipelines using LangChain to interface seamlessly with SAS VIYA offerings. * Integrate rigorous LLM defensive frameworks and operational Guardrails to ensure safe, compliant, and deterministic model behaviors across enterprise data. * Build and execute systematic validation frameworks to quantify LLM performance, tracking key metrics (such as context recall, faithfulness, and answer relevance) to ensure the highest output quality. * Embrace curiosity, passion, authenticity and accountability. These are our values and influence everything we do.