AI Engineer at ACCESA

We are looking for a hands-on AI Engineer to build production-ready AI solutions across Machine Learning and Generative AI use cases. The role focuses on implementation and technical delivery: developing LLM-powered applications, building ML models, integrating AI capabilities into enterprise systems, and improving the reliability, performance, and maintainability of deployed solutions.   Responsibilities   • Develop and maintain AI solutions using both Machine Learning and Generative AI approaches, aligned with business and client needs. • Build and improve LLM-based applications, including prompt engineering, orchestration flows, and tool usage. • Implement and optimize RAG pipelines, including chunking, embeddings, ranking, and retrieval strategies. • Work with vector databases such as pgvector, FAISS, Pinecone, or Weaviate to support semantic search and context-aware responses. • Develop integrations using MCP or similar approaches to connect AI systems with external tools, APIs, and enterprise platforms. • Train, evaluate, and deploy ML models for prediction, classification, clustering, or other data-driven use cases. • Contribute to API development and integration of AI capabilities into existing applications and workflows. • Support deployment, monitoring, and optimization of AI services in cloud and/or on-premise environments. • Implement basic guardrails, validation, and monitoring mechanisms to improve quality, reliability, and safe usage of AI systems. • Deploy, configure, and support AI workloads in Azure, AWS, or GCP, using cloud services for compute, storage, networking, security, and monitoring. • Collaborate with cross-functional teams including software engineers, data scientists, and business stakeholders to deliver production-ready solutions. • Stay up to date with relevant developments in AI, ML, and GenAI, and contribute to knowledge sharing within the team.