Key skills
AI systems developmentLLMsgenerative AIMLOps pipelinesCloud-based AI toolsPrompt engineeringAIMachine LearningMLGenerative AIOpenAIClaudeGeminiLlamaRAGAgenticAutoGenMLOpsAWSAzureGCPBedrockVertex AISaaSLeadership
About this role
3E is a mission-driven company dedicated to creating a safer and more sustainable world through regulatory expertise and cutting-edge technology. As an AI Engineer, you will develop intelligent systems and frameworks that leverage AI to enhance product workflows and drive customer value, working closely with cross-functional teams and leadership.
Responsibilities:
- Lead Development of Secure, Autonomous AI Systems: Architect intelligent, agent-based tools leveraging solutions like Claude Code, MCPs, A2A, Gemini CLI, the OpenAI Agents SDK, and using Knowledge Graph concepts to solve complex, high-value problems
- Develop A2A Systems: Build frameworks to enable LLMs to work together internally and externally, increasing the reach of 3E-enabled generative AI systems
- Bridge Product & Engineering: Partner with Product, Engineering, and Customer teams to embed AI into tools that enhance usability, decision-making, and automation
- Build Seamless API Integrations: Create scalable, secure APIs that connect AI models with web applications, internal systems, and external platforms. Integrate these with MCP for agentic use
- Contribute to Responsible AI Practices: Stay current with AI advancements and help define responsible development standards, alignment strategies, and safety protocols
Requirements:
- Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent experience in developing and deploying production-grade AI systems or Software as a Service (SaaS systems) as a Software Engineer or Machine Learning engineer (or similar role)
- Deep experience developing and deploying production-grade AI systems as a Software Engineer or Machine Learning engineer, or in a similar role
- Hands-on experience with LLMs, generative AI, and agentic frameworks such as MCP, A2A, and the OpenAI Agents SDK
- Proven ability in AI infrastructure setting up production-grade model inference serving, MLOps pipelines, and shared services
- Solid understanding of AI safety, alignment, and ethical development practices
- Master's degree or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field
- Experience with agent orchestration frameworks such as Claude Subagents, AutoGen, or CrewAI
- Expertise in prompt engineering, context engineering, RAG pipelines, and optimization
- Expertise in using and deploying open-source LLMs into production, such as variants of Qwen, DeepSeek, Llama, Mistral, Gemma
- Familiarity with cloud-based AI tools (e.g., AWS Bedrock, GCP Vertex AI, Azure ML)
- Experience integrating AI capabilities into legacy web applications, desktop applications, and APIs