Role overview
We are seeking a skilled AI Engineer with a strong focus on Generative AI technologies to develop, optimize, and deploy AI Agents and solutions. The role involves working on real-world use cases and data analytics problems and delivering production-ready AI systems.
Responsibilities
- Design, develop, and optimize Generative AI solutions (LLMs, RAG systems, AI agents).
- Fine-tune, evaluate, and deploy large language models for enterprise use cases.
- Build and maintain end-to-end AI pipelines, from data ingestion to inference.
- Implement Retrieval-Augmented Generation (RAG) using vector databases and knowledge stores.
- Integrate GenAI solutions with existing systems via APIs and microservices.
- Optimize model performance, latency, and cost on cloud platforms (OCI, AWS, Azure, or GCP).
- Collaborate with product, data, and engineering teams to translate business needs into AI solutions.
- Ensure AI solutions follow best practices in security, governance, and responsible AI.
- Stay up to date with the latest developments in GenAI, LLMs, and AI tooling.
- Minimum 5 years of professional experience in AI / Machine Learning.
- Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field.
- Proficiency in programming languages such as python , Java , and Ruby.
- Strong experience with Large Language Models (LLMs) (e.g., GPT, LLaMA, Mistral, etc.).
- Hands-on experience with Python and AI/ML frameworks (PyTorch, TensorFlow).
- Solid understanding of NLP, deep learning, and transformer architectures.
- Experience with RAG architectures, vector databases (FAISS, OpenSearch, Pinecone, etc.).
- Strong software engineering skills (APIs, REST, microservices, Docker, Kubernetes).
- Experience deploying AI workloads on cloud platforms (OCI preferred).
- Excellent problem-solving and analytical skills.
- Excellent command of English (written and spoken).
Preferred qualifications
- Experience with GPU-based training and inference.
- Familiarity with MLOps / LLMOps practices.
- Experience in regulated or enterprise environments.
- Knowledge of AI governance, ethics, and compliance frameworks.
Benefits
- Opportunity to work on cutting-edge Generative AI projects.
- Collaborative, innovation-driven environment.
- Competitive compensation package.
- Access to modern AI infrastructure and cloud resources.
- Professional growth and learning opportunities.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Remote Ai Ai Engineer Generative Ai