Strong understanding of the AI development lifecycle from experimentation to production deployment
Experience with modern LLM platforms and APIs such as OpenAI, Anthropic, Amazon Bedrock, or Google Gemini
Knowledge of advanced AI system architectures including Retrieval-Augmented Generation (RAG) and AI agents
Experience deploying scalable AI solutions with attention to performance, reliability, and cost efficiency
Requirements:
Design and develop AI-powered applications and intelligent automation solutions
Work with clients and internal stakeholders to identify opportunities where LLM-based solutions can deliver value
Build and maintain data pipelines, prompt architectures, and datasets that support effective AI models
Evaluate and optimize AI systems for accuracy, reliability, scalability, and security
Job description
This is a remote position.
RichBrains is looking for a proactive AI Engineer to take full ownership of AI initiatives, architect and implement advanced solutions that support development workflows, knowledge systems, and intelligent agent-based automation.
In this role, you will design scalable AI systems powered by modern LLMs while collaborating closely with clients and internal teams to translate business challenges into practical AI-driven solutions. You will play a key role in researching emerging LLM technologies and applying them to deliver high-impact products. This is an opportunity to deepen your expertise in AI engineering while building reliable, production-grade AI systems tailored to real-world business needs.
Responsibilities
Design and develop AI-powered applications and intelligent automation solutions;
Work with clients and internal stakeholders to identify opportunities where LLM-based solutions can deliver value;
Build and maintain data pipelines, prompt architectures, and datasets that support effective AI models;
Evaluate and optimize AI systems for accuracy, reliability, scalability, and security;
Validate technical approaches while ensuring solutions provide measurable business impact;
Stay current with advancements in LLM technologies, frameworks, and best practices to continuously improve implementations;
You strive to be proactive and responsible for your decisions, lead discussions and contribute your ideas, without waiting for instructions.
Requirements
Strong understanding of the AI development lifecycle from experimentation to production deployment;
Experience working with modern LLM platforms and APIs such as OpenAI, Anthropic, Amazon Bedrock, or Google Gemini;
Knowledge of advanced AI system architectures including Retrieval-Augmented Generation (RAG) and AI agents;
Experience deploying scalable AI solutions with attention to performance, reliability, and cost efficiency;
Ability to evaluate generative AI outputs using techniques such as retrieval validation, classification, or LLM-based evaluation methods;
Proven experience delivering AI or machine learning solutions in production environments;
Strong analytical and problem-solving skills with high attention to detail;
Good written and spoken English communication skills (B2 or higher).
Nice to have
Experience designing experiments and performing A/B testing to improve model performance;
Knowledge of retrieval systems, vector databases, and ranking techniques;
Experience deploying AI systems on cloud platforms such as Azure OpenAI or Amazon Bedrock;
Familiarity with enterprise AI platforms like AWS AgentCore, Databricks AgentBricks, or Azure AI Foundry;
Experience with monitoring, observability, and evaluation tools for AI systems.
Benefits
Collaborating with a highly motivated and professional team, which values your ideas and expertise;
Enjoying a dynamic work environment, where you'll be empowered with diverse tasks and the freedom to make decisions;
Taking part in corporate events that bring the team together and strengthen team spirit;
Accessing select corporate perks and discounts;
Working hours 11:00-20:00 with remote or hybrid options.
