Product Engineering Lead (AI Platform)
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Job Summary
Our client is looking for a hands-on Engineering Lead who owns its own AI Platform technical execution architecture code quality and delivery across three AI abilities areas: Document AI RAG and Agentic AI Platform. Writes code reviews code and personally implements the most critical components. Must handle AI-specific non-functionals: model latency token cost retrieval quality agent reliability evaluation discipline. Collaborates with AI Research Lead on model selection and retrieval quality.
What You Own:
- Farabi technical architecture: service decomposition retrieval-pipeline design agent-framework design evaluation harness security deployment topology.
- Hands-on implementation of architecturally sensitive performance-critical and security-sensitive AI components.
- Architecture decision log: model adoption vector-DB choice agent-framework selection evaluation methodology. Visible to CEO CTO AI Research Lead GPM.
- PMEngineering loop: demand measurable acceptance criteria for AI features ("90% precision on test corpus" not "should be accurate"). Refuse unmeasurable requirements.
- Code review and engineering quality bar correctness security evaluation discipline cost impact.
- Lead and mentor the Mid Full Stack Engineer. Grow the engineering practice.
- AI non-functional posture: latency baselines token cost per request evaluation harness for RAG quality and agent reliability.
- Security and data posture: what customer data goes to which LLM provider PII handling on-prem/hybrid for data-sensitive clients.
- Reliability: incident command for AI Sev1s (model degradation hallucination spikes agent loops LLM provider outages).
Requirements
What You Bring:
- 7 years software engineering 3 at senior/lead level on production software products.
- Strong backend foundation ( or Java) with full-stack capability.
- Production AI/LLM experience: has shipped at least one production AI feature (RAG extraction classification agent workflow) and lived with its operational reality. Veto if absent.
- Production experience across React Angular MS SQL MongoDB PostgreSQL LLM API integration at least one vector DB.
- Application architecture ownership for an enterprise web application or AI platform.
- Database and retrieval design: relational vs document vs vector stores. Has built or operated a retrieval pipeline.
- API integration with LLM providers enterprise systems. Understands model-provider rate limits and failover.
- Performance and cost troubleshooting in an AI system (latency runaway token costs).
- Code review and real engineer mentoring (specific person specific growth arc).
- AI-engineering daily usage (Copilot Claude Code Cursor). Tested live in Stage 3.
- Configurable-product instinct multi-customer shared codebase.
- Egyptian or Middle East enterprise context.
- ArabicEnglish bilingual at professional level.
Nice-to-Have:
- NLP document understanding information retrieval or knowledge-graph engineering background.
- On-premises LLM deployment or hybrid AI architectures.
- AI evaluation and benchmarking: golden-set discipline A/B testing of prompts and retrieval strategies.
- Agent frameworks at production scale (LangGraph AutoGen CrewAI custom orchestrators).
- Security certification or formal training.
Required Skills:
5 years of experience in marketing roles with at least 23 years in a leadership capacity Strong background in B2B digital services consulting tech or venture ecosystems Proven experience managing and leading external marketing agencies Solid understanding of digital marketing demand generation and brand strategy Data-driven mindset with strong analytical and reporting skills Excellent communication and stakeholder management skills Fluency in English (Arabic is a strong plus) What Success Looks Like Clear consistent brand positioning across all entities High-performing agencies delivering measurable results Marketing directly supporting revenue growth and business objectives Strong visibility and credibility within the startup tech and innovation ecosystem Marketing operating as a strategic growth engine not a support function
