
Artificial Intelligence Engineer
2 days ago
Job Type: contract / permanent (Full-time)
Job Description :
We're seeking a highly skilled AI/ML Engineer with expertise in building scalable, intelligent conversational systems and agent frameworks. The ideal candidate will have a strong background in containerized AI agents, semantic kernel development, observability, data management, API gateway deployment, and large language model (LLM) integrations to drive innovative VRM solutions.
Key Responsibilities:
- Develop and maintain containerized AI agents using frameworks like Langgraph, LangChain, and LangFuse.
- Implement semantic kernel solutions in Python for intelligent language processing.
- Design and optimize MCP tooling workflows without direct API calls, ensuring efficient tooling development.
- Define protocols for agent-to-agent (A2A) communication, ensuring reliable and scalable interactions.
- Implement observability solutions using Langfuse, Observe, and Obstacle for system monitoring and debugging.
- Integrate Retrieval-Augmented Generation (RAG) techniques leveraging DynamoDB, Bedrock, and embedding models for knowledge retrieval.
- Engineer context management and dialogue state tracking using Aurora DB.
- Build and deploy CI/CD pipelines for efficient agent deployment and updates, utilizing Docker, ECS Fargate, and FastAPI.
- Implement LLM as an arbitration or judgment system with ChatGPT-4 and OpenAI APIs.
- Manage container orchestration with ECS Fargate and Docker.
- Configure and optimize API Gateway layers with Kong Gateway for secure and scalable API management.
- Develop strategies to tackle agent scalability and performance challenges in large-scale environments.
Qualifications:
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or related fields.
- Proven experience in building AI-powered agent systems with frameworks like LangChain, Langgraph, LangFuse.
- Strong Python development skills, especially in semantic kernel and NLP applications.
- Hands-on experience with DynamoDB, AWS Bedrock, embedding models, and RAG methodology.
- Deep knowledge of containerization (Docker), orchestration (ECS Fargate), and deployment pipelines (CI/CD).
- Familiarity with large language models (e.g., GPT-4, OpenAI API) as decision or judgment components.
- Experience with API management tools such as Kong Gateway.
- Expertise in system observability and monitoring (Langfuse, Observe, Obstacle).
- Knowledge of SQL/NoSQL databases, especially Aurora DB, for context and dialogue management.
- Strong problem-solving capabilities in scaling and optimizing agent architectures.
- Excellent communication and collaboration skills in a fast-paced environment.
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