L3 Artificial Intelligence (AI) Developer

Design, develop, and implement AI-powered applications and intelligent automation solutions.
Build, integrate, and deploy Machine Learning and Generative AI solutions into enterprise applications.
Develop AI services and APIs that integrate seamlessly with existing business systems.
Collaborate with Data Engineers, Solution Architects, Business Analysts, and application development teams to deliver AI-driven solutions.
Develop and optimize prompts, AI workflows, and retrieval mechanisms for Generative AI applications.
Fine-tune, evaluate, and monitor AI models to ensure performance, reliability, and accuracy.
Develop scalable backend services supporting AI and machine learning workloads.
Participate in technical design, code reviews, testing, deployment, and production support.
Ensure AI solutions follow enterprise security, governance, and responsible AI practices.
Stay up to date with emerging AI technologies and recommend innovative solutions to business challenges.
Mentor junior developers and promote engineering best practices across the team.

Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, or a related field.
8–10 years of experience in software development or application development.
At least 3–4 years of hands‑on experience developing AI, Machine Learning, or Generative AI solutions.
Strong proficiency in Python and experience building enterprise‑grade applications.
Experience integrating AI capabilities into web, cloud, or enterprise applications.
Experience working with Large Language Models (LLMs) and modern AI frameworks.
Familiarity with frameworks and libraries such as LangChain, LangGraph, Semantic Kernel, Hugging Face, TensorFlow, PyTorch, or scikit-learn.
Experience consuming AI services such as Azure OpenAI, OpenAI APIs, Azure AI Services, AWS Bedrock, or Google Vertex AI.
Strong understanding of REST APIs, microservices, and software architecture principles.
Experience with Git, CI/CD pipelines, Agile/Scrum methodologies, and modern software development practices.
Excellent analytical, problem-solving, and communication skills.

Experience implementing Retrieval-Augmented Generation (RAG) solutions.
Experience with vector databases such as Pinecone, Azure AI Search, Weaviate, Chroma, or Milvus.
Experience with Docker, Kubernetes, or cloud‑native deployments.
Familiarity with MLOps concepts and AI model lifecycle management.
Experience with Microsoft Azure, AWS, or Google Cloud Platform.
AI, Azure, AWS, or cloud-related certifications are an advantage.

See also