Generative AI Engineer

About the role

We are looking for an AI Engineer to design, develop, and deploy innovative Generative AI applications that solve real-world business and customer problems.

The ideal candidate has strong software engineering fundamentals and hands-on experience building applications powered by large language models (LLMs), AI agents, and modern machine learning technologies.

You will work closely with product, engineering, and data teams to transform AI concepts into reliable, scalable, and production-ready solutions. Key

Design and develop Generative AI applications using LLMs and modern AI frameworks.

Build AI-powered features including conversational assistants, intelligent automation, document processing, and AI agents.

Develop and integrate LLM APIs, embeddings, vector databases, and retrieval-augmented generation (RAG) pipelines.

Create effective prompting strategies and evaluate model outputs for accuracy, relevance, and reliability.

Develop scalable APIs and backend services to support AI applications.

Integrate AI solutions with existing products, platforms, and third-party services.

Implement evaluation, monitoring, logging, and guardrails for production AI systems.

Optimize AI applications for performance, scalability, cost, and latency.

Collaborate with product managers, designers, data scientists, and software engineers to deliver end-to-end AI solutions.

Stay current with advancements in Generative AI, LLMs, agentic systems, and machine learning.

Required Qualifications

Bachelor’s degree in Computer Science, Engineering, Artificial Intelligence, or a related technical field.

Experience developing software applications using Python or another modern programming language.

Hands-on experience working with Generative AI, LLMs, or machine learning applications.

Experience with REST APIs, cloud platforms, databases, and software development best practices.

Understanding of prompt engineering, embeddings, vector search, and RAG architectures.

Strong problem-solving and debugging skills.

Ability to work effectively in a fast-paced, collaborative technology environment.

Preferred Qualifications

Experience with OpenAI, Anthropic, Google Gemini, or other foundation-model APIs.

Experience with frameworks such as LangChain, LlamaIndex, or similar AI application frameworks.

Familiarity with vector databases such as Pinecone, Weaviate, Milvus, or pgvector.

Experience building AI agents and tool-using LLM applications.

Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.

Familiarity with Docker, CI/CD, Kubernetes, or other modern deployment technologies.

Experience with AI evaluation, observability, safety, and responsible AI practices.