AI Software Engineer (2026-3281)

Prolink; United States; Remote; USD 110,000 - 180,000; Full time

Job summary

Prolink in the United States is seeking an AI Software Engineer to develop, integrate, deploy, and support AI-enabled applications and automations across the organization. This hands-on role turns business needs and designs into reliable production solutions within the enterprise AI architecture.

You will collaborate with stakeholders and IT teams to understand requirements, test solutions, troubleshoot issues, and monitor performance, adoption, and governance.

Qualifications

• Bachelor's degree in Computer Science, IT, Software Eng or related field.
• 3+ years of professional software engineering or application development experience.
• Hands-on experience developing AI, generative AI, machine learning, intelligent automation, or advanced analytics solutions.
• Proficiency in Python, C#, Java, or JavaScript/TypeScript.
• Experience building and consuming REST APIs, web services, JSON payloads, webhooks, and system integrations.
• Experience with cloud platforms, source control, testing, debugging, deployment, monitoring, and production support practices.
• Working knowledge of authentication and authorization methods, secure coding principles, data privacy, and enterprise integration patterns.
• Ability to understand business requirements, communicate technical tradeoffs, and independently execute development work

Responsibilities

• Design and build AI-enabled applications, agents, copilots, and automations based on approved requirements and technical patterns.
• Develop, test, and troubleshoot production-quality code using appropriate programming languages, frameworks, and software engineering practices.
• Build retrieval-augmented generation solutions, including document ingestion, chunking, embeddings, vector search, grounding, and response orchestration.
• Create reusable components, prompts, tools, and services that support consistent solution delivery.
• Evaluate solution performance, accuracy, reliability, latency, and cost; make improvements based on testing and production results.
• Develop and maintain REST APIs, web services, JSON payloads, webhooks, and system integrations.
• Implement authentication, data transformation, error handling, logging, and monitoring in accordance with established enterprise standards.
• Translate documented business and technical requirements into working solutions, estimates, development tasks, and test plans.
• Create prototypes and proofs of concept, then harden validated solutions for deployment and ongoing use.
• Participate in code reviews, testing, release management, deployment, and production support activities.
• Monitor deployed solutions, investigate defects and performance issues, and implement fixes and enhancements.
• Maintain technical documentation, configuration details, support procedures, and reusable development guidance.
• Partner with users and IT teams to validate outcomes, support adoption, and identify practical improvements.

Skills

Software engineering

AI development

REST APIs

Cloud platforms

Secure coding

Requirements analysis

Independent execution

Education

Bachelor's degree in Computer Science or related field

Tools

Python

Java

JavaScript/TypeScript

C#

CI/CD

Job description

Job Summary

The AI Software Engineer develops, integrates, deploys, and supports AI-enabled applications and automations across the organization. This is a hands-on engineering role for someone who can independently turn defined business needs and technical designs into reliable production solutions.

Working within the enterprise AI architecture, technical standards, security requirements, and governance established by IT leadership, this role builds AI applications, agents, APIs, integrations, retrieval-augmented generation solutions, and workflow automations. The engineer partners with business stakeholders and IT teams to understand requirements, develop and test solutions, troubleshoot issues, and support ongoing performance and adoption.

Responsibilities

AI Application Development

• Design and build AI-enabled applications, agents, copilots, and automations based on approved requirements and technical patterns.


• Develop, test, and troubleshoot production-quality code using appropriate programming languages, frameworks, and software engineering practices.


• Build retrieval-augmented generation solutions, including document ingestion, chunking, embeddings, vector search, grounding, and response orchestration.


• Create reusable components, prompts, tools, and services that support consistent solution delivery.


• Evaluate solution performance, accuracy, reliability, latency, and cost; make improvements based on testing and production results.

APIs Integrations and Data

• Develop and maintain REST APIs, web services, webhooks, and integrations connecting AI solutions with enterprise applications and data sources.


• Implement authentication, data transformation, error handling, logging, and monitoring in accordance with established enterprise standards.


• Work with structured and unstructured data and collaborate with data, application, infrastructure, and security teams to resolve integration dependencies.


• Build solutions that securely access and use enterprise data within approved access controls, privacy requirements, and governance guardrails.

Solution Delivery and Support

• Translate documented business and technical requirements into working solutions, estimates, development tasks, and test plans.


• Create prototypes and proofs of concept, then harden validated solutions for deployment and ongoing use.


• Participate in code reviews, testing, release management, deployment, and production support activities.


• Monitor deployed solutions, investigate defects and performance issues, and implement fixes and enhancements.


• Maintain technical documentation, configuration details, support procedures, and reusable development guidance.


• Partner with users and IT teams to validate outcomes, support adoption, and identify practical improvements.

Standards Security and Responsible AI

• Develop solutions within the AI architecture, technical standards, security controls, and governance framework established by IT leadership.


• Apply secure coding, data protection, testing, and responsible AI practices throughout the development lifecycle.


• Identify technical, security, data, or model risks and elevate design decisions or exceptions to the appropriate architecture, security, or governance owners.


• Contribute implementation feedback and lessons learned to help improve shared engineering patterns and standards.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Software Engineering, Information Systems, or a related field, or equivalent practical experience.


• 3+ years of professional software engineering or application development experience, including experience delivering and supporting production solutions.


• Hands-on experience developing AI, generative AI, machine learning, intelligent automation, or advanced analytics solutions.


• Proficiency in at least one general-purpose programming language commonly used for AI development, such as Python, C#, Java, or JavaScript/TypeScript.


• Experience building and consuming REST APIs, web services, JSON payloads, webhooks, and system integrations.


• Experience with cloud platforms, source control, testing, debugging, deployment, monitoring, and production support practices.


• Working knowledge of authentication and authorization methods, secure coding principles, data privacy, and enterprise integration patterns.


• Ability to understand business requirements, communicate technical tradeoffs, and independently execute development work

Preferences

• Experience with platforms or services such as Azure AI, Azure OpenAI, Microsoft Copilot Studio, OpenAI, Anthropic, Google Gemini, AWS AI Services, or similar technologies.


• Experience building AI agents, tool-calling workflows, prompt orchestration, and retrieval-augmented generation solutions.


• Experience with vector databases, semantic search, embeddings, model evaluation, observability, or AI safety tooling.


• Experience integrating with enterprise platforms such as Microsoft Dynamics, Workday, Power Platform, Databricks, or similar business applications.


• Experience with Azure integration and application services, containerized applications, CI/CD pipelines, or infrastructure automation.


• Familiarity with responsible AI practices, model risk, data governance, and human-in-the-loop review patterns.

Candidates with additional and relevant experience, education, licensing, or certification beyond the role's requirements and/or specific to the nature of Prolink's business will be given additional consideration in the candidate selection process. If all minimum requirements are met, candidates with unique and/or diverse qualifications will also be given additional consideration.