About the job
Our Mission
At Datacom, we bridge the gap between technology and people, striving to tackle challenges, unlock opportunities, and explore new horizons for our communities.
Role Overview
In light of rapid technological advancement, Datacom is seeking a Technical Business Analyst with a comprehensive focus on AI. Your objective will be to connect innovative AI technologies with tangible business results. You will be integral in crafting AI-driven solutions, ensuring that intelligent systems are meticulously designed, documented, and implemented to deliver significant business benefits.
Key Responsibilities
Requirements Gathering & AI Solution Development
- Analyze client business processes, identifying challenges and opportunities where AI and automation can add value
- Gather and document requirements for AI/ML solutions, detailing model inputs/outputs, training data needs, and business rules
- Identify and document AI use cases, including LLM integrations, predictive analytics, intelligent automation, and conversational AI workflows
- Chart data flows among AI models, consumers, and providers across interconnected systems
Documentation & Deliverable Creation
- Develop and oversee JIRA tickets that include:
- Acceptance criteria
- Implementation specifications
- AI model behavior expectations and edge case scenarios
- Consumer/provider mappings
- Document all solution deliverables in Confluence, covering:
- UML sequence diagrams for AI-integrated workflows
- Integration design patterns (AI APIs, model endpoints, orchestration layers)
- Prompt engineering guidelines and LLM behavior specifications
- Mapping tables, endpoints, and environment configurations
- Postman collections for AI API testing
- Acceptance criteria for AI model outputs and responses
AI-Oriented Facilitation & Team Collaboration
- Conduct workshops and discovery sessions aimed at identifying AI opportunities and scoping solutions
- Facilitate 3 Amigos sessions (Dev, Tester, and BA) with a focus on AI model validation, bias considerations, and ethical AI outcomes
- Work alongside Data Scientists and ML Engineers to convert business requirements into model specifications
- Promote responsible AI principles, ensuring ethical considerations, explainability, and compliance are integral to solution design
Data & Integration Architecture
- Define data model requirements essential for AI/ML training processes and inference outputs
- Document HTTP protocols and integration standards for AI systems...
