About the Role We are looking for an innovative AI Architect who will lead the design and
implementation of Agentic AI, Generative AI (GenAI), and Large Language Model (LLM) -
driven solutions across enterprise applications. The ideal candidate will bridge research
and production
Key Responsibilities
- Architect and design end-to-end AI systems leveraging LLMs, GenAI, and Agentic AI
- frameworks.
- Define AI/ML solution architecture involving data ingestion, model training,
- orchestration, and deployment across Azure / AWS / GCP.
- Work on prompt engineering, RAG (Retrieval-Augmented Generation), and fine tuning of
- open-source and proprietary LLMs (GPT, Claude, Gemini, LLaMA, etc.).
- Collaborate with data scientists, MLOps engineers, and software developers to
- operationalize AI solutions in production environments.
- Design and implement AI agent workflows, leveraging frameworks like LangChain,
- LlamaIndex, Haystack, or Semantic Kernel.
- Ensure responsible AI principles, focusing on security, compliance, and ethical model
- usage.
- Define AI governance and observability frameworks for tracking model drift, bias, and
- performance.
- Stay updated on Agentic AI, multimodal AI, and self-learning systems, and evaluate
- emerging GenAI tools and APIs for business adoption.
- Provide technical leadership and mentorship to AI teams, guiding solution design,
- architecture reviews, and best practices.
Required Skills & Experience
10+ years of experience in software development, with at least 4+ years in AI/ML/GenAI
architecture.
- Strong proficiency in Python, TensorFlow / PyTorch, and transformer-based architectures
- (BERT, GPT, T5, etc.).
- Proven experience with LLM integration, prompt engineering, RAG, and vector databases
- (FAISS, Pinecone, Chroma, Milvus).
- Hands-on experience with LangChain, LlamaIndex, OpenAI / Azure OpenAI, or similar
- LLM orchestration tools.
- Solid understanding of MLOps pipelines, CI/CD, and model deployment using Azure
- Machine Learning, SageMaker, or Vertex AI.
- Knowledge of API orchestration, microservices, and containerization (Docker,
- Kubernetes).
- Experience in integrating GenAI capabilities into enterprise apps (chatbots, copilots,
- document intelligence, code assistants, etc.).
- Strong analytical, communication, and solution design skills.
Work Location: In person
