Here’s a summary of the role:

Ready to build real-world AI solutions that actually make an impact?

You’ll take cutting-edge AI and GenAI concepts—like copilots, agents, and intelligent workflows—and turn them into scalable, production-ready systems used across sales, finance, customer success, and more. If you enjoy hands-on backend engineering, working with APIs, cloud platforms, and LLMs, and transforming ideas into high-performing AI-driven products, this role puts you right at the center of innovation.

Here’s a breakdown of what you’ll do (not all of it, just the important stuff):

• Build and scale backend services, APIs, and integrations that embed AI/GenAI into enterprise systems (CRM, ERP, BI)
• Develop LLM-powered solutions such as RAG pipelines, copilots, agents, and automation workflows
• Take AI solutions from concept to production—design, build, test, deploy, and monitor
• Collaborate with architects and business stakeholders to turn requirements into practical AI implementations
• Create and manage data pipelines to enable reliable, high-quality AI workflows
• Ensure solutions are secure, scalable, observable, and aligned with best practices

These are the essentials you’ll need to get an interview:

• 5+ years of experience in software or solutions engineering with production systems
• Strong programming skills in Python, Java, C#, or Node.js
• Hands-on experience with APIs, integrations (REST/webhooks), and backend development
• Practical experience working with LLMs/GenAI tools (e.g., OpenAI, LangChain, or similar)
• Experience with cloud platforms (preferably AWS), CI/CD, and containerization
• Solid understanding of AI/GenAI concepts like prompt engineering, RAG, or agents
• Ability to translate technical solutions into business impact and collaborate across teams

It would be great if you had these too, but we’ll support you if you don’t:

• Experience integrating AI into CRM, ERP, or analytics platforms
• Familiarity with MLOps/LLMOps concepts such as model lifecycle and monitoring
• Exposure to machine learning or data analytics tools (e.g., Scikit-learn, dashboards)
• Experience working in global or distributed teams
• Knowledge of AI governance, security, and responsible AI practices

The Team:

Our Business Applications and Analytics team plays a pivotal role in driving business success through data-driven decision-making and operational excellence. This dynamic team manages enterprise-wide applications, including ERP, CRM, and BI systems. By harnessing the power of data and advanced analytical tools, we provide valuable insights that inform strategic initiatives, optimize processes, and enhance overall performance.  

Position Overview:  

Diligent is ‘All-In’ on AI and is seeking a dynamic and strategic AI leader to join our team as an AI Solutions Architect. As part of the Business Applications and Analytics team, this crucial role is designed to accelerate our Internal AI capabilities across multiple business functions, including Marketing, GTM/Sales, Customer Success & Support, Finance, HR, Legal, and Product and Engineering teams. 

The primary goal of this position is to identify, prototype, deploy, and scale AI technologies and solutions that drive greater operational efficiency and effectiveness. The ideal candidate will be a technically adept individual with business acumen, able to bridge the gap between robust technical implementations and business needs, with the ability to partner with various business leaders to spot and act on opportunities for AI-driven transformation and innovation. 

Key Responsibilities:

• Partner with business leaders to understand challenges, identify AI opportunities, and implement effective AI/GenAI solutions.
• Lead the ideation, prototyping, deployment, and scaling of AI/GenAI technologies and agentic solutions tailored to business needs.
• Develop and communicate strategic frameworks and roadmaps for AI initiatives aligned with business goals.
• Champion best practices in AI/ML and GenAI development—including responsible AI, privacy, security, and ethical guidelines.
• Collaborate with cross-functional teams to integrate AI tools within core business processes, ensuring seamless, high-value adoption.
• Stay abreast of AI best practices, tools, and methodologies and introduce them to the organization.
• Drive AI and Data literacy across the company through training, workshops, and continuous education initiatives.
• Ensure compliance with data protection and privacy regulations in all AI implementations.
• Monitor and evaluate the performance and effectiveness of AI solutions and continually refine them.
• Collaborate with stakeholders to define and achieve key performance indicators (KPIs) and return on investment (ROI) for AI projects.
• Advocate and implement AI ethical guidelines and best practices.

Required Qualifications:

• Solid Foundations: Bachelor’s degree in Computer Science, AI/ML, Data Science, or a related technical field.
• Practical Tinkerer: 5+ years in a technical role (software, data, DevOps, etc.), with hands on experience building end-to-end prototypes using GenAI tools (GPTs, Hugging Face, open-source LLMs, LangChain, Scikit-learn, etc.).
• Curious Explorer: Demonstrates a hands-on approach to learning in prompt-engineering, fine-tuning, RAG pipelines, or API Integrations, with a commitment to rapid failure, iteration, and sharing findings.
• Data Wrangler: Possesses the ability to source, clean, and transform raw data, including spreadsheets, logs, APIs, or CRM exports, into structured inputs for AI experiments and prototypes.
• Code Crafter: Capable of writing scripts or small applications to connect models, cloud services, or data sources. Prior experience with TensorFlow, PyTorch, Azure, AWS, or GCP is beneficial, but willingness to learn is equally important.
• Business Translator: Experienced as a technical sales engineer or solutions consultant, capable of turning AI experiments into compelling stories and metrics that resonate with non-technical stakeholders.
• Responsible AI Mindset: Demonstrated experience in addressing privacy, security, bias, and ethics in professional work, with a strong familiarity with industry-specific data privacy, AI ethics, and compliance requirements.
• Team Player: Essential qualities include clear communication and a growth mindset, as you will collaborate with marketers, sales professionals, engineers and leaders.

Preferred Qualifications:

• Demonstrates strong knowledge of AI use cases, including NLP, computer vision, data analytics, predictive modelling, and translating technical capabilities into business value, along with proficiency in large language models (LLMs), prompt engineering, RAG architectures, MLOps, LLMOps, and GenAI application deployment.
• Advanced programming and data engineering skills, with Python preferred, and experience in cloud-based AI solutions (AWS, GCP, Azure).
• Ability to architect and deploy enterprise-scale AI solutions, collaborating across sales, product, and implementation teams to ensure adoption and measurable ROI.
• Strategic thinker with strong analytical and problem-solving skills, capable of driving measurable business outcomes through AI/GenAI.