senior ai engineer ( Work from Home)TSG Outsourcing

How to Apply:
 
Copy and Paste the Link below in the browser to generate the application form:
https://forms.gle/6jCzuQw2WhQsN3Kf8
 
Rate: $12/hr and earn up to PHP 120,000+/month
Schedule: Monday - Friday: 8:30 AM - 5:00 PM PST with 30-Minute Unpaid Lunch break and Two 15-Min Paid Breaks
 
SENIOR AI ENGINEER (WORK FROM HOME)
 
About the Role
 
We're looking for a Founding AI Engineer to build intelligent, autonomous AI agents for cybersecurity. You'll work across our entire AI stack-from prompt engineering and context assembly to multi-agent orchestration and evaluation systems.
 
This is an early-stage founding role where you'll shape how AI solves real security problems. If you love building with LLMs and want to be there from day one, this is for you.
 
Responsibilities:
Design and implement autonomous AI agents with reasoning and tool-use capabilities
Build context engineering (RAG/CAG) pipelines for consistent, grounded agent outputs
Design inference orchestration systems for multi-step agent workflows
Create multi-agent systems with role specialization and orchestration
Implement agent memory systems, evaluation frameworks, and monitoring
Work with security experts to encode domain knowledge into agent architectures
Ship AI features end-to-end: from prototype to production
Must Have Qualifications:
 
Core Skills
Strong hands-on experience building with LLMs in production (Claude, GPT-4, Gemini)
Experience with agent frameworks: LangGraph, LangChain, AutoGen, or CrewAI
Expert-level prompt engineering: few-shot, chain-of-thought, ReAct patterns
Context engineering: chunking strategies, indexing, reranking, and retrieval systems
Prompt management: versioning, evaluations, traces, and deployment workflows
LLMOps and observability: monitoring, debugging, and optimizing LLM applications
Experience with Langfuse or similar LLM observability platforms
Vector databases (Pinecone, Weaviate, Qdrant, Chroma, FAISS)
Understanding of LLM APIs, function calling, and structured outputs
Knowledge graphs, ontologies, and graph databases
Expert Python and building scalable APIs (FastAPI, Flask)
SQL/NoSQL systems, async patterns, message queues, event-driven architectures
AI security: prompt injection mitigation, guardrails, output validation
Performance optimization and cost management for LLM applications
Designing systems for reliability and scalability
Exposure to DevOps and deployment technologies: Docker, Kubernetes, AWS/GCP/Azure
Exposure to Multi-tenant SaaS architecture and data isolation
Technical Stack
Languages: Python 3.x, JavaScript, Go
Agent Frameworks: LangGraph, LangChain, LlamaIndex, AutoGen
LLM APIs: Claude, OpenAI, Gemini
Vector DB:
Pinecone, Weaviate, Qdrant, Chroma, FAISS
LLMOps: Langfuse (observability, prompt management, tracing)
ML Libraries: Hugging Face, sentence-transformers
API: FastAPI, Flask
Infrastructure: AWS/GCP/Azure, Docker
Nice To Have Qualifications:
You've owned significant AI features or systems end-to-end
You move from vague ideas to shipped features independently
You care about code quality, testing, and system reliability
Experience with model fine-tuning, RLHF, LoRA, or domain adaptation
GPU optimization and inference acceleration (vLLM, TensorRT)
Open-source contributions or technical writing