AI Developer

AI Developer

We are searching for people who have experience building advanced AI systems that power intelligent automation, telecom-scale data solutions, and next-generation network tools. You will work on cutting-edge generative AI, prompt engineering, and Retrieval-Augmented Generation (RAG) architectures, helping teams integrate and scale AI capabilities across key product lines. This role blends software engineering excellence with deep AI model experience in real-world applications.

What You’ll Do

• Design, build, and deploy AI-driven solutions using Java and Python in production environments.
• Develop Generative AI applications that leverage large language models and neural frameworks.
• Lead the creation and optimization of RAG workflows (vector search, retrieval services, embedded search).
• Craft and refine prompts to ensure high-quality, context-aware interactions from language models.
• Collaborate with cross-functional teams (data engineering, architecture, product stakeholders).
• Implement scalable APIs, microservices, and modular model components.
• Integrate AI solutions across cloud platforms and distributed systems.
• Contribute to performance testing, validation, deployment, and model monitoring.

Required Skills & Experience

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Machine Learning, or related field.
• Strong software engineering experience with Java and/or Python.
• Demonstrated experience building or integrating Generative AI models.
• Knowledgeable in RAG approaches, including embeddings and vector database integration.
• Practical prompt engineering experience with major LLM platforms or frameworks.
• Familiarity with modern AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain).
• Comfortable with APIs, REST, microservices, containers (Docker, Kubernetes).
• Excellent analytical and communication skills.

Preferred Qualifications

• Experience with ML engineering best practices (MLOps, model CI/CD pipelines).
• Familiarity with cloud environments (e.g., AWS, Azure, GCP).
• Knowledge of vector search engines or embedding databases (e.g., Pinecone, Weaviate, Milvus).
• Telecom or large-enterprise system integration experience.
• Exposure to large-scale data pipelines and distributed systems.

Key skills/competency

• Generative AI
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Java
• Python
• Machine Learning
• Deep Learning
• LLMs
• Vector Databases
• Cloud Platforms