Artificial Intelligence Engineer

Role & responsibilities

• Build and maintain Generative AI applications using LLM APIs, prompt workflows, RAG pipelines, and agent-based orchestration.
• Develop backend services, APIs, and microservices in Python using frameworks such as FastAPI or Flask.
• Implement use cases such as enterprise assistants, document Q&A systems, internal copilots, workflow automation tools, and tool-using AI agents.
• Integrate AI applications with enterprise systems, databases, APIs, and external tools.
• Collect, clean, preprocess, and structure datasets used for AI workflows, retrieval pipelines, evaluation, and application inputs.
• Develop and maintain data and feature pipelines that support retrieval quality, model inputs, inference workflows, and application consistency
• Support preparation of knowledge sources for RAG systems, including chunking, indexing, metadata design, and retrieval optimization.
• Implement MCP-style tool usage patterns, connectors, APIs, and tool-enabled workflows where applicable.
• Participate in testing, evaluation, logging, monitoring, debugging, and ongoing improvement of AI applications.
• Help optimize AI systems for latency, response quality, hallucination reduction, robustness, and token efficiency.

Preferred candidate profile

• Bachelors degree in computer science, Artificial Intelligence, Data Science, Engineering, or a related field.
• 5 years of experience in software engineering, applied AI, ML engineering, or related development roles.
• Hands-on experience with one more cloud technology - Microsoft, AWS, Google
• Strong hands-on experience in 2 more skills - Python, Pyspark, Node.js, React, Angular, Flask
• Good practical understanding of LLM-based applications and Generative AI implementation.
• Experience with some of the following: prompt engineering, RAG pipelines, vector databases, agent frameworks, API integration, Python backend development, and data preparation or workflow pipelines.
• Familiarity with frameworks and tools such as LangChain, LangGraph, CrewAI, Phidata, LlamaIndex, or similar.
• Experience building REST APIs or backend services using FastAPI, Flask, or similar frameworks.
• Good understanding of JSON, structured data flows, APIs, and service-oriented design.
• Proficiency in SQL and relational databases, along with experience in managing unstructured data using NoSQL or vector databases for AI model training and retrieval.
• Strong problem-solving skills and willingness to learn quickly