Companies in this catalog do not charge applicants. Never send money to apply.
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
