Senior AI Platform Engineer

• Strong experience in Python for AI model integration, automation, and orchestration logic
• 1–2 years hands-on experience with Generative AI and large language models (LLMs)
• Practical machine learning engineering skills including data preparation, vector databases in cloud, and model training/optimization
• Expertise in agentic evaluation frameworks for complex multi-agent systems, including reasoning traces and tool selection
• Proven experience designing automated testing and evaluation gates within CI/CD pipelines for AI models
• Strong backend and frontend architecture experience
• Experience with cloud platforms such as AWS, GCP, or Azure, container orchestration, and CI/CD pipelines
• Experience with agentic frameworks like LangChain and LangGraph and multi-agent system design
• Comfort with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn is a plus

• Develop and launch scalable conversational AI systems operating across chat, voice, email, and APIs
• Architect microservices and asynchronous systems for AI applications ensuring high availability and performance
• Use Python to implement orchestration and decision logic managing tools, workflows, and system interactions
• Design agentic evaluation frameworks tracking multi-step workflows, tool-calling accuracy, and session performance
• Integrate automated gates into CI/CD pipelines
• Establish automated evaluation protocols using LLM-as-a-judge patterns
• Optimize AI models via fine-tuning and LoRA integration, making data-driven decisions between fine-tuning and retrieval-augmented generation
• Collaborate with data specialists on pipelines for collecting, cleaning, and structuring information for AI agents
• Design CI/CD pipelines, container standards, and cloud strategies for infrastructure migration, cost optimization, and high availability

Benefits listed are for employees only; B2B contractors negotiated individually; only selected candidates will be contacted.