Overview
The role involves designing, developing, and deploying AI and machine learning solutions, including LLM-powered applications and agentic AI workflows, to enhance investigative capabilities.
Key Responsibilities
- Design, develop, and deploy AI and machine learning solutions on Microsoft Azure, including LLM-powered applications for natural language querying, automated summarization, entity extraction, and Retrieval-Augmented Generation pipelines.
- Develop agentic AI workflows that autonomously execute multi-step investigative tasks such as cross-referencing communications, mapping entity relationships, and generating analytical briefings.
- Build interactive dashboards and web-based front-end applications to visualize investigation metrics, case analytics, and AI processing outputs.
- Create dynamic data visualization tools enabling investigators to explore evidence of relationships and communication patterns.
- Develop and deploy intelligent chatbot interfaces for natural language querying of case evidence, communications data, and forensic outputs.
- Implement safeguards, access controls, and audit trails to ensure secure and ethical use of AI in sensitive investigative contexts.
- Design automation workflows using Microsoft Power Automate, Azure Logic Apps, and Python scripts; develop and maintain API integrations with forensic tools and internal systems.
- Provide technical guidance and coordination for AI Integration interns, including task assignments, code review, onboarding, and quality assurance.
- Contribute to sprint planning, progress reporting, and support the Head of Digital Forensics & AI Integration in strategic planning and technology assessment.
- Maintain comprehensive technical documentation, user guides, and training materials for all developed systems, workflows, and integration procedures.
Required Experience
- Minimum of one (1) year of relevant professional experience in AI/ML development, software engineering, or data science.
- Demonstrated experience developing applications using Python, with proficiency in frameworks such as Flask, Fast API, or Django.
- Experience working with cloud platforms, preferably Microsoft Azure (Azure OpenAI, Azure AI Search, Azure Functions, Azure Blob Storage).
- Experience with large language model integration, prompt engineering, and Retrieval-Augmented Generation architectures.
- Experience with API development and integration (REST APIs, webhooks).
- Understanding data security principles, particularly in handling sensitive and confidential information.
Qualifications
- Bachelor's degree in computer science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a related field from a recognized university.
- A master’s degree is an advantage.
