AI Engineer
Jobs for Humanity Open · verified Oct 24, 2026 At a glance
Mid-level AI Engineering role at Jobs for Humanity. Remote, Lebanon · full-time.
Pay not stated AI Engineer salary
remoteroles summary, based on the employer's posting.
What you'll do
- Build LLM workflows that handle prompts, manage context and combine model responses
- Create systems where multiple AI agents coordinate, use tools and produce connected results
- Connect foundation model APIs, balancing response speed, operating cost and reliability
- Add retrieval and memory features, then test output quality and factual grounding with the QA engineer
- Ship and maintain features across model and application layers, improving performance and safeguards
What you bring
- At least three years in software engineering, including hands-on development of applications powered by LLMs
- Strong Python or TypeScript/JavaScript skills, plus practical experience with LLM APIs and prompt design
- Experience with agent frameworks, retrieval systems and vector databases such as Pinecone or another listed option
- Knowledge of multi-agent behavior, tool use, function calls and testing unpredictable AI outputs
Who this fits
This mid-level role suits a software engineer who has built LLM applications and wants to work across AI systems and production software. The position is remote and based in Beirut.
From the employer
About the Role
We're looking for an AI Engineer to design, build, and scale the systems that power our AI-driven product. You'll work at the intersection of large language models, multi-agent systems, and production software, turning cutting-edge AI capabilities into reliable, user-facing experiences.
What You'll Do
- Design and implement LLM-powered pipelines, including prompt engineering, context management, and response synthesis
- Build and optimize multi-agent orchestration systems where AI components interact, reason, and produce coherent outputs
- Develop and maintain integrations with foundation model APIs (Anthropic, OpenAI, and others), managing latency, cost, and reliability at scale
- Implement retrieval-augmented generation (RAG) and memory systems for persistent, context-aware behavior
- Partner with the Evaluation/QA Engineer to build frameworks that measure output quality, coherence, and factual grounding
- Collaborate with product and design to translate workflows into robust technical experiences
- Ship production features across the stack, from the model layer to the application
Monitor, debug, and improve system performance, token efficiency, and guardrails
- 3+ years of software engineering experience, with hands-on work building LLM-powered applications
- Strong proficiency in Python and/or TypeScript/JavaScript
- Experience with LLM APIs, prompt engineering, and agentic frameworks (e.g., LangChain, LlamaIndex, or custom orchestration)
- Familiarity with vector databases and RAG architectures (Pinecone, Weaviate, pgvector, etc.)
- Understanding of multi-agent systems, tool use, and function calling
- Experience designing evaluation and testing strategies for non-deterministic AI outputs
- Solid grasp of API design, async processing, and scalable backend architecture
- Comfort working in a fast-moving, ambiguous, early-stage environment
- Experience with real-time streaming (WebSockets, SSE) for conversational interfaces
- Background in fine-tuning, model distillation, or inference optimization
- Familiarity with cloud infrastructure (AWS/GCP/Azure) and CI/CD
- Contributions to open-source AI projects
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