Role Overview Responsible for building prescriptive and generative AI components that translate model outputs into actionable business recommendations. Bridges the gap between data science outputs and production-ready business deliverables.
Experience Required: 3–5 years
Key Responsibilities
- Build prescriptive and optimisation engines using mathematical programming and heuristic solvers
- Design,
develope and implement LLM solutions within secure enterprise infrastructure
- Engineer LLM prompts to generate plain-language business narratives and ranked recommendations
- Build automated report generation pipelines delivering structured outputs to business consumers
- Integrate ML model outputs with generative AI components for consistent and explainable end-to-end delivery
- Build rule-based trigger engines and exception management workflows
- Support A/B testing frameworks to compare AI-driven vs. baseline recommendations
- Design and implement impact analysis and counterfactual simulation capabilities
Required Skills
- 3–5 years of experience in AI/ML engineering, software engineering, or applied AI development
- Experience with mathematical optimisation
(
PuLP
, OR-Tools, linear programming)
- Proficiency in LLM prompt engineering and self-hosted or API-based model deployment
- Familiarity with LLM frameworks (
LangChain
, Hugging Face, OpenAI API)
- Robust Python skills and experience building automated data and reporting pipelines
- Knowledge of NLP and generative AI techniques
- Experience with supply chain or inventory optimisation preferred