Senior Applied AI/Generative AI Specialist (6-10 yrs)

Job Description :

Key Responsibilities :

- Design, develop, and deploy production-ready AI and Generative AI applications.

- Build intelligent solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and multimodal AI technologies.

- Develop scalable AI workflows using frameworks such as LangChain, LlamaIndex, Semantic Kernel, or similar orchestration tools.

- Integrate AI solutions with enterprise applications, APIs, databases, cloud platforms, and Microsoft ecosystem technologies.

- Fine-tune prompts and optimize model performance for accuracy, latency, and cost efficiency.

- Collaborate with business stakeholders to identify AI use cases and translate requirements into technical solutions.

- Develop secure and responsible AI solutions, ensuring compliance with governance, privacy, and ethical AI standards.

- Build and maintain vector databases, knowledge retrieval pipelines, and semantic search capabilities.

- Monitor AI application performance, troubleshoot production issues, and continuously improve model effectiveness.

- Mentor junior engineers and contribute to AI best practices, reusable components, and technical standards.

- Stay current with emerging AI technologies, research, and industry trends to drive innovation.

Required Qualifications :

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

- 6- 10 years of software engineering experience, with at least 3 years focused on AI/ML or Generative AI.

- Strong proficiency in Python and modern software development practices.

- Hands-on experience with OpenAI, Azure OpenAI Service, Anthropic, Google Gemini, or other enterprise LLM platforms.

- Experience building applications using RAG, vector databases (Azure AI Search, Pinecone, FAISS, ChromaDB, or similar), and embedding models.

- Strong understanding of prompt engineering, AI agents, function calling, tool integration, and LLM evaluation techniques.

- Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud.

- Knowledge of REST APIs, Docker, Kubernetes, Git, CI/CD pipelines, and MLOps practices.

- Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications :

- Experience with Azure AI Foundry, Azure Machine Learning, Microsoft Copilot Studio, or enterprise AI platforms.

- Knowledge of fine-tuning, model evaluation, guardrails, AI observability, and Responsible AI frameworks.

- Experience integrating AI solutions with Microsoft Dynamics 365, Microsoft 365, Power Platform, or enterprise business applications.

- Relevant AI, Azure, or cloud certifications are an advantage.

Key Competencies :

- Generative AI Solution Development

- Large Language Models (LLMs)

- Retrieval-Augmented Generation (RAG)

- AI Agents & Prompt Engineering

- Python Development

- Cloud AI Architecture

- API & Enterprise Integration

- MLOps & AI Deployment

- Responsible AI & Governance

- Technical Leadership & Mentoring