- Company Name
- Unlimitail
- Job Title
- Strategic AI Product Engineer
- Job Description
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**Job Title:** Strategic AI Product Engineer
**Role Summary:**
Architect and strategist who translates complex business challenges into end‑to‑end AI solutions for retail media. Drives the AI roadmap, builds high‑impact AI features, and enables cross‑functional adoption across product, engineering, data, and operations.
**Expectations:**
- Own end‑to‑end AI initiatives from concept to production.
- Influence strategy, prioritisation, and governance across the organisation.
- Act as an internal AI consultant, advising on feasibility, ROI, and risk.
- Deliver measurable business value through AI‑enabled products and processes.
- Foster a culture of experimentation and responsible AI use.
**Key Responsibilities:**
- Define and execute the AI strategy, identifying high‑impact problems in product, operations, media activation, and customer experience.
- Design AI solution architectures (LLM agents, automation flows, classification, prediction, optimisation) and prototype with open‑source models, cloud services, or third‑party APIs.
- Lead AI discovery sessions, map workflows, identify quick wins, produce MVPs, and scale deployments.
- Build reusable components, templates, and internal tools to accelerate AI adoption.
- Establish evaluation frameworks (accuracy, latency, robustness, safety, resources), monitor production systems, and iterate for continuous improvement.
- Collaborate with Data Engineering, Product, and Operations to deliver full AI workflows and ensure integration with microservices and cloud environments.
- Communicate findings and recommendations to both technical and non‑technical stakeholders, maintaining clear documentation and knowledge sharing.
**Required Skills:**
- 5+ years in software engineering, ML/AI engineering, data engineering, or technical consulting.
- Strong engineering fundamentals (coding, architecture, APIs, microservices).
- Proficiency with modern AI stacks: LLMs, embeddings, vector databases, agent frameworks, orchestration tools.
- Experience prototyping AI features and building end‑to‑end workflows.
- Solid understanding of cloud environments, integration patterns, and observability.
- Consulting‑style problem‑solving: translate ambiguous business problems into structured AI solutions.
- Excellent communication skills in English; able to present technical concepts to non‑technical audiences.
- Strategic mindset: evaluate feasibility, ROI, constraints, risks, and governance for AI initiatives.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related technical field.
- Optional: certifications in AI/ML (e.g., TensorFlow, AWS AI Services, Microsoft Azure AI) strengthen the application.