Associate AI Software Engineer

Asure Software • Austin, TX

6d • Onsite

About The Position

As an Associate AI Software Engineer, you will work alongside experienced engineers and AI practitioners to design, develop, test, and maintain AI-powered software that supports Asure's products and platform services. In this role you will primarily write Python and build features that integrate large language models (LLMs) and other AI services into real applications running in our AWS cloud environment. This role is designed for early-career engineers who are eager to grow by learning modern AI software development practices and contributing to business-critical applications. You will gain hands-on experience integrating LLMs, building the APIs and data pipelines that support AI features, and applying solid software engineering fundamentals — all with the guidance and support of a senior team, and with room to grow your skills over time. Much of this work supports Asure's agentic AI platform, which is designed to turn AI reasoning into reliable, real-world execution across payroll and HCM workflows — with human confirmation required before any sensitive action is committed. You will help build the tools and integrations that let AI systems take safe, well-scoped actions rather than simply generating text, working with modern agent architectures such as the Model Context Protocol (MCP) and human-in-the-loop patterns.

Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Artificial Intelligence, Information Technology, or a related technical field.
• Understanding of software development fundamentals, including object-oriented programming, data structures, algorithms, and software design principles.
• Proficiency in Python — the primary language for this role — demonstrated through coursework, projects, internships, or personal development.
• Strong fundamentals in another modern language (e.g., C#, Java, or JavaScript/TypeScript) with the ability to ramp up quickly on Python are also welcome.
• Foundational understanding of artificial intelligence, machine learning, or generative AI concepts, gained through coursework, certifications, projects, research, internships, or personal learning.
• Understanding of large language models (LLMs) and basic prompt engineering concepts, and how they are applied in software applications.
• Familiarity with APIs and web services.
• Familiarity with at least one major cloud platform (AWS preferred; Azure or Google Cloud Platform also relevant).
• Basic understanding of data management concepts, including relational and NoSQL databases.
• Experience using Git or other version control systems.
• Strong problem-solving, analytical, and communication skills.
• Ability to learn quickly and collaborate effectively in a team-oriented environment.

Nice To Haves

• Hands-on experience — through work, internships, co-ops, academic or personal projects, hackathons, or open-source contributions — building software that uses LLMs or other AI capabilities.
• Experience building agentic AI features — including agent orchestration, tool/function calling, and the Model Context Protocol (MCP) — or with related frameworks and patterns such as LangChain, retrieval-augmented generation (RAG), vector databases, and embeddings.
• Exposure to LLM platforms and services such as Anthropic, Amazon Bedrock, OpenAI, Azure OpenAI, or Google Gemini.
• Hands-on experience with AWS, particularly its AI/ML and application services (e.g., Amazon Bedrock, SageMaker, Lambda, DynamoDB).
• Exposure to the Python data and ML ecosystem (e.g., Pandas, NumPy, and libraries such as PyTorch, TensorFlow, or Scikit-learn).
• Familiarity with RESTful APIs, web services, and third-party or system integrations.
• Understanding of AI model and prompt evaluation, monitoring, governance, security, and responsible AI principles.
• Familiarity with Agile methodologies, DevOps practices, automated testing, or CI/CD pipelines.
• Exposure to data engineering, ETL pipelines, or analytics platforms.
• Experience using AI-assisted development tools such as GitHub Copilot, Cursor, or similar.

Responsibilities

• Collaborate with engineers, product managers, and other stakeholders to build AI-powered software features that meet business and customer needs.
• Write clean, maintainable, well-tested Python code for applications, services, and APIs that leverage AI and LLM capabilities.
• Integrate large language models (LLMs) and AI services into software applications and business workflows, primarily within our AWS environment.
• Assist with prompt design, experimentation, evaluation, and validation of LLM-based features under the guidance of senior engineers.
• Contribute to the data pipelines and retrieval components (e.g., embeddings and vector search) that support AI features.
• Participate in code reviews and incorporate feedback to improve software quality, AI solution effectiveness, and your own technical skills.
• Assist with troubleshooting, debugging, monitoring, and resolving defects in AI-enabled applications and services.
• Work with relational, NoSQL, and vector data stores to support AI-driven solutions.
• Support the deployment and operation of AI applications and services in cloud (AWS) environments.
• Participate in Agile development activities, including sprint planning, stand-ups, and retrospectives.
• Follow software engineering and responsible AI best practices, and continuously develop your knowledge across Python, AI/LLMs, and cloud technologies with a curiosity and growth mindset.

Benefits

• Medical, Dental, Vision, HSA, FSA- All effective on day 1!
• Company paid Basic Life Insurance, A+D, Long-Term Disability, and Short-Term Disability
• 401K Program with 3% safe harbor contribution
• Employee Stock Purchase Program
• Fitness Reimbursement Program
• Self-Managed PTO

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level