AI ENGINEER

About The Role Focus We are looking for an experienced AI Engineer to design, build, integrate, and deploy AI-powered solutions for real-world products.

The ideal candidate will have strong hands-on experience with Generative AI, Large Language Models (LLMs), AI APIs, AI application architecture, and production AI systems . This role requires an engineer who can take AI capabilities beyond experimentation and turn them into reliable, scalable, and production-ready product features.

You will work across AI solution design, data and model integration, backend services, user-facing applications, deployment, monitoring, and continuous improvement.

Strong software engineering capabilities are essential, as the role involves building the application layers required to deliver AI solutions in production. The candidate should be comfortable working with backend APIs, frontend applications, databases, mobile application integration, cloud environments, and modern development workflows.

Key Responsibilities

• Design and develop production-ready AI solutions based on business and product requirements.
• Build AI-powered features using Generative AI, Large Language Models, machine learning services, and AI APIs.
• Design AI workflows involving prompt engineering, context management, retrieval, tool calling, function calling, and multi-step processing.
• Develop intelligent features such as AI assistants, chatbots, recommendations, summarization, classification, semantic search, content generation, automation, and decision-support workflows.
• Design and implement Retrieval-Augmented Generation (RAG) solutions and integrate relevant enterprise or product data into AI workflows.
• Work with embeddings, vector search, vector databases, and semantic retrieval systems.
• Build and integrate AI agents and tool-based workflows where appropriate.
• Evaluate AI outputs and continuously improve accuracy, reliability, relevance, latency, and cost efficiency.
• Select appropriate models and AI services based on use case, quality, performance, scalability, and cost requirements.
• Integrate AI capabilities into web and mobile applications through APIs and application services.
• Develop backend services and APIs required to support AI features and application functionality.
• Collaborate with frontend and mobile developers to deliver AI-powered user experiences.
• Work with databases, data pipelines, and application data required by AI systems.
• Participate in architecture discussions and make technical decisions related to AI application design.
• Own AI features end-to-end, from requirement analysis and technical design through development, testing, deployment, monitoring, and production support.
• Investigate and resolve production issues involving application behavior, AI responses, integrations, performance, and data.
• Stay current with emerging AI models, frameworks, tools, and development practices and assess their practical value for products.

Required Skills & ExperienceAI Engineering

• Strong hands-on experience with Generative AI and Large Language Model applications.
• Experience working with OpenAI, Google Gemini, Anthropic, or equivalent AI model providers.
• Strong understanding of prompt engineering and structured prompt design.
• Practical experience building RAG-based applications.
• Experience with embeddings, vector databases, semantic search, and retrieval pipelines.
• Experience with AI agents, function calling, tool calling, or agentic workflows.
• Experience with LangChain, LlamaIndex, Semantic Kernel, or similar AI development frameworks is preferred.
• Strong understanding of model context windows, token usage, latency, scalability, and AI cost optimization.
• Ability to evaluate AI outputs and improve response quality, consistency, and reliability.
• Understanding of hallucination mitigation, grounding, validation, and responsible AI practices.
• Experience integrating AI services into production applications through APIs.
• Strong Python programming skills and familiarity with relevant AI/ML libraries and frameworks.
• Understanding of data preparation, preprocessing, and fundamental machine learning concepts.
• Exposure to model evaluation, observability, prompt/version management, and AI quality monitoring is an advantage.

Software Engineering & Application Development The AI Engineer should also have strong software engineering skills to build and int…