AI Engineer

As an AI Agent Engineer, you will be responsible for designing scalable AI systems, integrating LLMs, and building backend infrastructure for intelligent automation. Your key responsibilities will include: - Designing, developing, and deploying multi-agent AI systems using LLMs and reasoning frameworks like Meta's Coral. - Architecting and implementing Agent-to-Agent (A2A) communication protocols and lifecycle management systems. - Building and optimizing RAG (Retrieval-Augmented Generation) pipelines integrated with vector databases. - Collaborating with backend teams to integrate AI services with REST/gRPC APIs. - Contributing to prompt engineering and model tuning for specific business use cases. - Developing AI-driven chat interfaces using React and ensuring a seamless user experience. - Working with client teams to deliver custom AI consulting solutions and proof-of-concept implementations. The core requirements for this role include: Core AI Agent Development: - Strong understanding of multi-agent systems and LLM integrations. - Familiarity with reasoning frameworks like Meta's Coral. - Hands-on experience with agent lifecycle management. - Expertise in prompt engineering and RAG systems. - Knowledge of Coral Mediation. Backend Platform and Services: - Strong in REST and gRPC APIs. - Proficient in FastAPI and NATS JetStream. - Experience with PostgreSQL, MongoDB, and Redis. - Solid grasp of database design and data flow between services. Frontend, UX, and Interaction Design: - Experience building AI-driven Chat UIs with React. Authentication: - Knowledge of OAuth 2.0 and OIDC. Preferred Qualifications: - Prior experience working on agentic AI, LLM orchestration, or AI infrastructure tools. - Exposure to LangChain, LlamaIndex, or OpenAI function calling APIs. - Experience in consulting or client-facing delivery projects. As an AI Agent Engineer, you will be responsible for designing scalable AI systems, integrating LLMs, and building backend infrastructure for intelligent automation. Your key responsibilities will include: - Designing, developing, and deploying multi-agent AI systems using LLMs and reasoning frameworks like Meta's Coral. - Architecting and implementing Agent-to-Agent (A2A) communication protocols and lifecycle management systems. - Building and optimizing RAG (Retrieval-Augmented Generation) pipelines integrated with vector databases. - Collaborating with backend teams to integrate AI services with REST/gRPC APIs. - Contributing to prompt engineering and model tuning for specific business use cases. - Developing AI-driven chat interfaces using React and ensuring a seamless user experience. - Working with client teams to deliver custom AI consulting solutions and proof-of-concept implementations. The core requirements for this role include: Core AI Agent Development: - Strong understanding of multi-agent systems and LLM integrations. - Familiarity with reasoning frameworks like Meta's Coral. - Hands-on experience with agent lifecycle management. - Expertise in prompt engineering and RAG systems. - Knowledge of Coral Mediation. Backend Platform and Services: - Strong in REST and gRPC APIs. - Proficient in FastAPI and NATS JetStream. - Experience with PostgreSQL, MongoDB, and Redis. - Solid grasp of database design and data flow between services. Frontend, UX, and Interaction Design: - Experience building AI-driven Chat UIs with React. Authentication: - Knowledge of OAuth 2.0 and OIDC. Preferred Qualifications: - Prior experience working on agentic AI, LLM orchestration, or AI infrastructure tools. - Exposure to LangChain, LlamaIndex, or OpenAI function calling APIs. - Experience in consulting or client-facing delivery projects.