AI Engineer

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.