AI Engineer

We are looking for an experienced AI Developer with 5–7 years of hands-on experience in artificial intelligence, machine learning, and generative AI technologies. The ideal candidate will be responsible for designing, developing, deploying, and optimizing AI-driven solutions that address real-world business problems.

The role requires strong programming skills, experience with modern AI/ML frameworks, and the ability to work across the complete AI development lifecycle.

• Design, develop, and deploy AI/ML solutions for business and product use cases.

• Build and optimize machine learning and deep learning models.

• Develop applications using Generative AI, Large Language Models (LLMs), and NLP.

• Work with LLM APIs, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG).

• Develop and integrate AI models into production applications and enterprise systems.

• Perform data preprocessing, feature engineering, model evaluation, and performance optimization.

• Collaborate with data scientists, software engineers, product managers, and business stakeholders.

• Implement scalable and reliable AI services using cloud and containerization technologies.

• Monitor deployed models and continuously improve accuracy, latency, scalability, and cost.

• Stay current with emerging developments in AI, GenAI, LLMs, and machine learning.

• 5–7 years of professional experience in AI/ML software development.

• Strong proficiency in Python and experience with software development best practices.

• Strong understanding of Machine Learning and Deep Learning concepts.

• Hands-on experience with frameworks such as PyTorch, TensorFlow, Scikit-learn, or equivalent.

• Practical experience with Generative AI and LLM-based applications.

• Experience with OpenAI, Azure OpenAI, Anthropic, Google Gemini, or similar LLM platforms.

• Strong knowledge of RAG, embeddings, vector databases, prompt engineering, and agentic AI.

• Experience with frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent.

• Experience with REST APIs and integrating AI capabilities into enterprise applications.

• Knowledge of databases such as PostgreSQL, MySQL, MongoDB, or similar.

• Experience with vector databases such as Pinecone, Weaviate, FAISS, Milvus, or equivalent.

• Familiarity with Docker, Kubernetes, CI/CD, and cloud platforms such as AWS, Azure, or GCP.

• Good understanding of model evaluation, monitoring, security, and responsible AI practices.

• Strong analytical, problem-solving, and communication skills.

• Experience building AI agents and multi-agent systems.

• Experience with fine-tuning or parameter-efficient tuning of LLMs.

• Knowledge of MLOps/LLMOps practices.

• Experience with cloud-native AI/ML services.

• Exposure to computer vision, speech AI, or multimodal AI.

• Experience taking AI/ML prototypes from POC to production.

• Contributions to open-source AI/ML projects or published technical work.