Company Overview

Black Box Network Services is a leading global communications system integrator specializing in designing, sourcing, implementing, and managing complex technology solutions. As part of our strategic transformation, Black Box is expanding its AI Center of Excellence (CoE) to deliver enterprise-grade AI solutions across multiple business domains.

The AI CoE focuses on building scalable, secure, and production-ready AI systems, establishing best practices for enterprise AI adoption, and integrating AI capabilities into core business platforms.

Role Summary

As an AI Engineer in the AI Center of Excellence (CoE), you will design, build, and integrate AI-driven solutions using pre-trained Large Language Models (LLMs), traditional machine learning techniques, and deterministic systems.

This role emphasizes applied Generative AI, enterprise integration, and end-to-end ownership, from user experience to backend services and AI orchestration. You will collaborate closely with business and technology teams to deliver production-ready AI solutions integrated with platforms such as ServiceNow, SAP, Salesforce, and Azure services.

Engineers in this role are expected to contribute to engineering standards, reusable AI components, and reference architectures, in addition to delivering high-quality solutions.

Key Responsibilities AI Solution Development

• Leverage pre-trained LLMs for conversational AI, document summarization, and enterprise knowledge retrieval.
• Design and implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data sources.
• Develop traditional ML models (classification, regression) and deterministic rule-based systems for structured use cases.
• Design and deploy AI agents for task automation and intelligent decision-making.
• Implement workflow orchestration using n8n, integrating AI services with ServiceNow, SAP, Salesforce, and Azure services.
• Build AI-specific logic and agent orchestration using LangChain (chains, tools, memory, RAG).

Full-Stack Development & UI/UX

• Design intuitive, responsive user interfaces for AI-enabled applications.
• Develop frontend components using ReactJS and Astro.
• Implement backend services using Python (FastAPI/Flask) and Node.js (TypeScript).
• Ensure seamless integration between UI, backend services, and AI workflows.
• Own features from design through deployment and production support.

Platform & Engineering Standards

• Contribute to defining and improving AI engineering standards, reusable components, and reference architectures.
• Collaborate with DevOps, security, and platform teams to align AI solutions with enterprise guidelines.
• Identify opportunities to improve developer productivity, tooling, and automation.

Agile Development & CI/CD

• Work in Agile/Scrum teams, participating in sprint planning, stand-ups, and retrospectives.
• Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions.
• Ensure adherence to best practices in code quality, testing, and version control.

LLMOps & Lifecycle Management

• Implement pipelines for deployment, monitoring, and lifecycle management of AI solutions.
• Apply AIOps techniques for performance monitoring and anomaly detection.
• Track experiments and models using Weights & Biases (W&B) or similar platforms.

Data Engineering & Enterprise Integration

• Collaborate with data teams to design and build ETL pipelines for structured and unstructured data.
• Ensure data quality, validation, and reliability of AI outputs.
• Integrate AI solutions with ServiceNow workflows, SAP modules, Salesforce, and Azure-native services.

AI Governance & Responsible AI

• Implement bias detection and mitigation mechanisms.
• Maintain model documentation, audit trails, and compliance artifacts.
• Ensure adherence to ethical and responsible AI principles.

Research & Innovation

• Experiment with emerging Generative AI capabilities and enterprise AI patterns.
• Explore hybrid AI approaches combining deterministic logic with probabilistic models.
• Contribute to internal PoCs, hackathons, and technical workshops.

Required Skills

• 3+ years of experience in AI/ML engineering or data science.
• Strong expertise in LLMs, RAG, prompt engineering, and classical ML techniques.
• Experience building AI agents and workflow orchestration (LangChain, n8n).
• Proficiency in Python and TypeScript/Node.js.
• Hands-on experience with ReactJS and Astro.
• Ability to deliver end-to-end full-stack solutions.
• Experience with PostgreSQL, Azure AI stack, and cloud-native deployments.
• Solid understanding of Agile development practices and CI/CD pipelines.
• Familiarity with REST/GraphQL APIs, Docker, Kubernetes, and containerized deployments.
• Knowledge of NLP, OCR, and enterprise integration patterns.

Preferred Skills

• Experience with Generative AI models (GPT, BERT, DALL·E, etc.) and their practical enterprise applications.
• Familiarity with LLMOps and AIOps frameworks.
• Azure or AI-related certifications (e.g., Microsoft Certified: Azure AI Engineer).
• Experience with responsible AI, bias mitigation, and compliance.
• Exposure to enterprise environments with governance, security, and compliance constraints.
• Experience or familiarity with Microsoft Power Platform, including Microsoft Copilot, Power Automate, and Power Apps, for implementing low- to medium-complexity AI-enabled and automation use cases.

About Black Box

Black Box is a leading technology solutions provider focused on accelerating customer success through innovation, ownership, transparency, and collaboration. With over 2,500 team members across 24 countries, Black Box delivers high-value solutions globally and is a wholly-owned subsidiary of AGC Networks.

Black Box is an equal opportunity employer and does not discriminate based on race, color, gender, age, disability, veteran status, or any other protected status.