- Company Name
- E-Solutions
- Job Title
- Artificial Intelligence Engineer
- Job Description
-
**Job Title:** Artificial Intelligence Engineer
**Role Summary**
Design, prototype, and deliver AI-driven analytics solutions for procurement and sourcing challenges. Drive projects from initial problem framing through to scalable production, collaborating with consulting, product, and engineering teams.
**Expectations**
* 8–10 years of professional experience, ≥3–4 years in applied AI or advanced analytics.
* Proven track record of taking AI/analytics concepts from PoC to production or scaled deployment.
* Comfortable in client‑facing, consulting‑style environments with evolving requirements.
* Prior exposure to procurement, supply‑chain, or enterprise operations highly advantageous.
**Key Responsibilities**
* Identify and formalise procurement problems, then build end‑to‑end analytic and AI PoCs.
* Apply appropriate methods (statistics, ML, optimization, LLMs) and iterate quickly based on stakeholder feedback.
* Produce defensible, executive‑ready outputs that support decision‑making.
* Design LLM‑based solutions for reasoning, classification, extraction, and multi‑step workflows; evaluate accuracy, explainability, reliability, and cost.
* Create lightweight prototypes (Jupyter, Streamlit/Gradio) to validate concepts in workshops.
* Work with engineering and product teams to align PoCs with scalability and production readiness.
* Develop reusable patterns, reference architectures, and accelerators for future AI initiatives.
**Required Skills**
* **Data Science & ML:** Python (pandas, numpy, scikit‑learn); regression, classification, clustering, feature engineering, model validation, basic time‑series analysis.
* **Advanced Analytics:** Optimization, simulation, scenario modeling; translate results into clear business insights.
* **LLM & AI Expertise:** Prompt design, embeddings, retrieval‑augmented generation (RAG), classification/extraction/summarization; integrate LLMs with structured data and rules; assess outputs for enterprise use.
* **Prototyping & Engineering:** Notebook workflows (Jupyter), demo tools (Streamlit, Gradio); modular code design, Git, basic APIs, data pipelines.
* **Professional Competencies:** Strong analytical judgment, clear communication to technical and non‑technical audiences, cross‑team collaboration, high ownership, bias toward experimentation and delivery.
**Required Education & Certifications**
* Bachelor's or Master’s degree in Computer Science, Data Science, Statistics, Operations Research, or related field.
* Certifications in AI/ML (e.g., Microsoft Certified: Azure AI Engineer Associate, Google Cloud Professional Machine Learning Engineer) desirable but not mandatory.