AI Software Engineer

PM Consulting; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

eBSI Export Academy seeks a forward-thinking AI Software Engineer to design, develop, and maintain AI-enabled software for industrial automation, bridging traditional software with advanced AI capabilities. You will build AI pipelines, integrate AI frameworks, and collaborate with global teams to deliver production-ready solutions.

The role requires strong programming in Python/C++, familiarity with design patterns, and experience in DevSecOps practices.

Qualifications

• Degree in Engineering, CS, AI, IT, or related field.
• Experience as a software developer with proficiency in C++, C#, Python or Java.
• Familiarity with SOLID design patterns.

Responsibilities

• Design and implement AI-based software stacks.
• Integrate AI technologies into production systems.
• Develop secure AI pipelines and backend services.
• Create front-end components that interact with AI services.
• Support full application lifecycle from development to deployment.
• Contribute to CI/CD and release engineering.
• Ensure architecture aligns with standards and security guardrails.
• Maintain documentation for extensibility.

Skills

Python

C++

C#

Java

GoF patterns

SOLID

CI/CD

Generative AI

PyTorch

TensorFlow

Education

Bachelor's or Master's in Engineering, Computer Science, Artificial Intelligence, IT or related field

Tools

Haystack

LangChain

Ollama

Job description

We are seeking a forward-thinking AI Software Engineer to join our global Systems and Software client. In this role, you will be at the forefront of designing, developing, and maintaining cutting-edge software solutions that integrate AI functionality into industrial automation applications. You will bridge the gap between traditional software features and advanced AI technologies, developing everything from core modules to end-user agents.

Key Responsibilities

AI Development & Integration

• Full-Stack Design: Design and implement comprehensive technology stacks for AI-based or AI-powered software applications.
• Production Integration: Seamlessly integrate AI technologies, including frameworks, libraries, and models, into production-ready software.
• Pipeline Development: Build secure AI pipelines and back-end services using modern algorithms and methodologies.
• Front-End Interaction: Develop front-end components and modules that interact directly with AI services and data stores.

Systems Engineering & Delivery

• End-to-End Execution: Support the full application lifecycle, including development, packaging, and deployment.
• DevSecOps Collaboration: Contribute to CI/CD pipelines and build/release engineering workflows.
• Architecture & Standards: Adhere to established architectural patterns, coding standards, and security guardrails while participating in rigorous code reviews.
• System Integrity: Ensure clean integration between user interfaces, backend services, and databases.

Innovation & Collaboration

• Applied Research: Stay current on the latest AI technologies to research, design, and deliver end-to-end solutions.
• Global Partnership: Collaborate with stakeholders and global teams to ensure all technical solutions align with broader business goals.
• Documentation: Maintain and update technical documentation to ensure software applications are easily understood and extensible.

Requirements

Education & Experience

• Degree: Bachelor's or Master's degree in Engineering, Computer Science, Artificial Intelligence, IT, or a related field.
• Software Development: Demonstrable experience as a software developer with proficiency in languages such as C++, C#, Python, or Java .
• Design Patterns: Familiarity with applying software design patterns, including SOLID or Gang of Four (GoF) .

Technical Skills

• AI Expertise: Strong understanding of machine learning algorithms, generative AI, and general AI concepts.
• Framework Proficiency: Experience with AI libraries and frameworks such as PyTorch or TensorFlow .
• Data Engineering: Knowledge of data pre-processing, feature engineering, prompt engineering, and model evaluation techniques.

Preferred Qualifications

• AI Tooling: Experience with frameworks like Haystack, LangChain, or Ollama .
• Modern Architectures: Familiarity with REST APIs , asynchronous systems, and distributed enterprise platforms.
• Responsible AI: Knowledge of security, bias mitigation, and responsible AI frameworks.
• Methodologies: Experience with Agile , Test-Driven Development (TDD), and DevSecOps best practices.