Gen AI Architect

· Lead the architecture, design, development, and deployment of GenAI solutions.

· Build production-grade applications using LLMs, RAG, AI agents, and agentic workflows.

· Develop solutions using Python, LangChain, LlamaIndex, and other GenAI frameworks.

· Implement vector search, embeddings, prompt engineering, and model evaluation.

· Integrate AI solutions with enterprise applications, APIs, databases, and cloud platforms.

· Establish best practices for AI security, governance, performance, scalability, and cost optimization.

· Implement monitoring, testing, CI/CD, MLOps, and LLMOps practices.

· Lead technical teams, mentor developers, and collaborate with business and technology stakeholders.

Experience: 10+ years overall, with 2+ years in Generative AI, · 10+ years of experience in software engineering, AI/ML, data science, or related fields.

· 2+ years of hands-on Generative AI implementation experience.

· Strong Python programming skills.

· Experience with LLMs and platforms such as OpenAI, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.

· Hands-on experience building RAG applications and AI assistants.

· Experience with LangChain, LlamaIndex, Hugging Face, or similar frameworks.

· Knowledge of vector databases such as Pinecone, FAISS, Weaviate, Chroma, or Azure AI Search.

· Experience with AI agents, prompt engineering, model evaluation, and hallucination mitigation.

· Understanding of cloud platforms, APIs, microservices, CI/CD, Docker, Kubernetes, and LLMOps.

· Strong technical leadership, communication, and stakeholder management skills.

Preferred Qualifications

· Experience with multi-agent systems and agentic AI.

· Knowledge of fine-tuning, multimodal AI, and synthetic data generation.

· Experience with AI governance, security, privacy, and regulatory compliance.

· Experience delivering enterprise AI solutions in financial services, healthcare, insurance, or other regulated industries.