Job Summary
Key Responsibilities
AI Solution Design & Development
- Design and develop AI-powered applications using Large Language Models (LLMs) and Generative AI technologies.
- Architect and implement Agentic AI solutions capable of autonomous reasoning, planning, and task execution.
- Translate business requirements into scalable AI solutions and technical architectures.
- Build end-to-end AI workflows integrating enterprise systems, APIs, databases, and knowledge repositories.
Agent Framework Development
- Develop and deploy AI agents using frameworks such as:
- LangChain
- LangGraph
- CrewAI
- AutoGen
- Semantic Kernel
- Microsoft Copilot Studio (preferred)
- Implement multi-agent orchestration, tool usage, memory management, and workflow automation.
- Optimize agent performance, reliability, and scalability.
LLM Engineering
- Work with foundation models from OpenAI, Azure OpenAI, Anthropic, Google, Meta, and other leading providers.
- Design and implement:
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- Fine-tuning strategies
- Vector databases and semantic search
- Knowledge-grounded AI systems
- Evaluate LLM performance and establish monitoring mechanisms.
Deployment & Operations
- Deploy AI applications in cloud environments (Azure preferred).
- Implement MLOps/LLMOps best practices for model lifecycle management.
- Ensure governance, security, compliance, and responsible AI principles are incorporated into solutions.
- Monitor production systems and continuously improve AI solution effectiveness.
Skill Requirements
Technical Skills
- Strong understanding of:
- Large Language Models (LLMs)
- Generative AI
- Agentic AI architectures
- Prompt Engineering
- RAG architectures
- Vector Databases
- Experience building AI agents using one or more industry-leading frameworks.
- Proficiency in Python and AI application development.
- Experience with REST APIs, microservices, and cloud-native development.
- Hands-on experience with Azure AI Services, Azure OpenAI, or equivalent AI platforms.
Experience
- 5+ years of software development experience.
- 2+ years of hands-on experience in Generative AI and LLM-based solution development.
- Proven experience deploying AI solutions in production environments.
- Experience designing AI solutions for enterprise business use cases.
Preferred Qualifications
- Microsoft Azure AI Engineer Associate or related certifications.
- Experience with Microsoft Copilot Studio and Microsoft 365 Copilot extensibility.
- Knowledge of machine learning, NLP, and deep learning concepts.
- Experience with Kubernetes, Docker, and CI/CD pipelines.
- Familiarity with Responsible AI, AI governance, and AI risk management frameworks.
Other Requirements
Understanding of LLMs, Experience AI agent framework development, Agent Design and Deployment AI solutions for Business use cases