AI Agent Developer
- Role
- AI / ML
- Experience
- Senior
- Employment
- Full-time
Open to PH only. Set where you work from to check your eligibility.
No BS summary
Senior AI/ML engineer to design, build and ship production autonomous AI agents and multi-agent systems. Must have 4+ years in AI/ML engineering, strong Python and experience with LangChain/CrewAI/AutoGPT, RAG on vector DBs, MCP and AI governance. Remote, Philippines-based candidate preferred (benefits mention PH HMO).
Core skills
Required skills
Optional skills
Key Responsibilities: Research, design, develop, and manage software applications end-to-end Build and deploy production-grade autonomous AI agents (not just prototypes) Design and implement RAG architectures backed by vector databases Develop and optimize multi-agent workflows and agentic systems Integrate large language models via API — OpenAI, Hugging Face, Azure AI Implement Model Context Protocol (MCP) to enable secure, governed data access for agents Own AI governance, model lifecycle management, and ongoing evaluation of deployed agents Apply AI safety controls: guardrails, content filtering, and risk mitigation Collaborate cross-functionally with developers, UX designers, and business/systems analysts Continuously optimize LLM performance, inference cost, and token usage Requirements Must-Have 4+ years in AI/ML engineering or advanced data science Demonstrated experience shipping autonomous AI agents into production, not just building demos Strong grounding in context engineering Hands-on experience with agent frameworks: LangChain, LangGraph, CrewAI, AutoGPT Experience building RAG systems on vector databases Strong Python skills plus fluency with AI/ML libraries (OpenAI, Hugging Face, Azure AI) Experience wiring LLMs into applications via API Working knowledge of AI governance, model lifecycle management, and evaluation frameworks Direct experience implementing or extending Model Context Protocol (MCP) Familiarity with AI guardrails and safety tooling Understanding of data privacy requirements, including PII/PHI handling Nice-to-Have Experience working in a law firm, legal operations, or legal tech environment Hands-on experience with AI tools such as LLMs (e.g., ChatGPT), automation platforms (Zapier, Make), OCR tools, or analytics platforms Background in marketing automation, lead generation systems, or paid ads optimization Experience with chatbots, call automation, or client intake systems Familiarity with document automation, legal research tools, or eDiscovery platforms Basic understanding of APIs, integrations, or no-code/low-code tools Experience building dashboards (e.g., Power BI, Tableau, Google Data Studio) Knowledge of data privacy, compliance, and security considerations in AI implementation Prior experience in a consulting, operations, or innovation-focused role System and Work Setup Requirements: A stable and high-speed internet connection preferably 25 MBPS or higher with backup in cases of power interruption or service provider issues. Own PC/laptop with 8GB RAM, and a processor of Core i5 / AMD Ryzen 3 / 2013 Mac equivalent or higher; Windows 10 or above / Catalina 10.15 or newer; with up-to-date web browsers, and security software, 500GB/128 SSD storage Headset/earphone with noise cancellation and webcam at 720p or higher resolution A designated, quiet, and well-organized workspace free from distractions to facilitate focused work Benefits Permanent remote work setup Competitive starting rate paid in USD Internet Allowance HMO insurance (PH) Paid US holidays Paid Vacation and Sick Leaves
What you'll do
- Research, design, develop, and manage software applications end-to-end
- Build and deploy production-grade autonomous AI agents (not just prototypes)
- Design and implement RAG architectures backed by vector databases
- Develop and optimize multi-agent workflows and agentic systems
- Integrate large language models via API — OpenAI, Hugging Face, Azure AI
- Implement Model Context Protocol (MCP) to enable secure, governed data access for agents
- Own AI governance, model lifecycle management, and ongoing evaluation of deployed agents
- Apply AI safety controls: guardrails, content filtering, and risk mitigation
- Collaborate cross-functionally with developers, UX designers, and business/systems analysts
- Continuously optimize LLM performance, inference cost, and token usage
What they require
- Must-Have: 4+ years in AI/ML engineering or advanced data science
- Demonstrated experience shipping autonomous AI agents into production, not just building demos
- Strong grounding in context engineering
- Hands-on experience with agent frameworks: LangChain, LangGraph, CrewAI, AutoGPT
- Experience building RAG systems on vector databases
- Strong Python skills plus fluency with AI/ML libraries (OpenAI, Hugging Face, Azure AI)
- Experience wiring LLMs into applications via API
- Working knowledge of AI governance, model lifecycle management, and evaluation frameworks
- Direct experience implementing or extending Model Context Protocol (MCP)
- Familiarity with AI guardrails and safety tooling
- Understanding of data privacy requirements, including PII/PHI handling
Benefits
- Permanent remote work setup
- Competitive starting rate paid in USD
- Internet Allowance
- HMO insurance (PH)
- Paid US holidays
- Paid Vacation and Sick Leaves