The Role
Own and deliver production AI capabilities over enterprise data, including retrieval, RAG, agents, tool calling, and natural language interfaces. Design scalable architectures, evaluation frameworks, regression suites, grounding checks, and guardrails. Collaborate with engineering, product, data, design, and business teams while addressing reliability, performance, data quality, and operational risks. The role requires strong Python and LLM engineering experience, with preferred expertise in self-hosted model serving, inference optimization, GPU management, fine-tuning, and Text-to-SQL.
Summary Generated by Built In
This is a remote position.
We are looking for a Senior AI Engineer to join our team and take ownership of key areas within our technology and data platform. Owns the AI layer: retrieval, agents, and natural language interfaces over enterprise data, with evaluation so quality is measured rather than demonstrated.
Key Responsibilities
• Own and deliver solutions within the scope of the role, from requirements and technical/design decisions through implementation and continuous improvement.
• Work closely with engineering, product, data, design, and business stakeholders to translate requirements into practical, scalable solutions.
• Apply strong engineering and/or domain expertise to build reliable, maintainable, and production-ready capabilities.
• Contribute to architecture, standards, documentation, quality, and technical decision-making appropriate to the role.
• Identify performance, scalability, data quality, usability, reliability, or operational risks and address them proactively.
• Collaborate across teams to ensure solutions integrate effectively with existing systems and platform components.
Requirements
• Experience: 5+ years of relevant professional experience.
• Strong hands-on experience with: LLM application engineering, RAG and retrieval architecture, embeddings and vector search, agent and tool calling systems, LLM evaluation, Python.
• Software or data engineering background, with at least two years building LLM based systems that reached production.
• Retrieval architecture: chunking, embeddings, vector and hybrid search, and why naive RAG fails on structured data.
• Agent or tool calling systems, including permissions, scoping, and guardrails.
• Evaluation practice: test sets, regression suites, hallucination and grounding checks.
• Comfortable working inside a data platform rather than calling a hosted API.
Preferred Qualifications
• Self hosted open weight model serving with vLLM or equivalent, inference optimisation, and GPU resource management.
• Fine tuning or adaptation of open weight models.
• Text to SQL or semantic layer work over a real data model.
Skills Required
- 5+ years of relevant professional experience
- Strong hands-on experience with LLM application engineering
- Strong hands-on experience with RAG and retrieval architecture
- Strong hands-on experience with embeddings and vector search
- Strong hands-on experience with agent and tool calling systems
- Strong hands-on experience with LLM evaluation
- Strong hands-on experience with Python
- Software or data engineering background
- At least two years building LLM-based systems that reached production
- Knowledge of chunking, embeddings, vector search, hybrid search, and RAG limitations for structured data
- Experience implementing permissions, scoping, and guardrails for agent or tool calling systems
- Experience creating test sets, regression suites, hallucination checks, and grounding checks
- Comfort working inside a data platform rather than only calling a hosted API
- Experience with self-hosted open-weight model serving using vLLM or equivalent
- Experience with inference optimization and GPU resource management
- Experience with fine-tuning or adapting open-weight models
- Experience with Text-to-SQL or semantic layer work over a real data model
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The Company
What We Do
Techsa is a Cairo-based software services and development company that builds technology solutions tailored to client needs. Its work combines custom and mobile-app development, IT consulting, and software innovation with IoT/data-management platforms and analytics, including AI/ML-driven analysis. It serves sectors such as water and wastewater, logistics, roads, and property maintenance, and also describes itself as a partner for recruiting, onboarding, and managing software teams.
