AI Engineering Architect

Key Responsibilities:

• AI Architecture Engineering
• Define and own AI reference architectures for generative AI agentic systems and AI augmented applications
• Architect scalable solutions using LLMs multi agent systems orchestration frameworks and AI pipelines
• Design AI platforms supporting model serving prompt management RAG and workflow orchestration
• Establish architectural standards for performance scalability reliability and cost efficiency
• Platform Engineering Integration
• Build reusable AI components for LLM integration vector search embeddings and inference services
• Enable secure and scalable deployment using Kubernetes serverless platforms and CI CD pipelines
• Integrate AI capabilities into enterprise systems using APIs SDKs and event driven architectures
• Collaborate with QE teams to embed AI into test automation test data generation and intelligent validation
• Engineering Governance Quality
• Define architectural guardrails for model lifecycle versioning monitoring and rollback
• Ensure adherence to non functional requirements including performance observability and fault tolerance
• Leverage observability tools to monitor model performance and drift
• Review designs and implementations for architectural compliance and code quality
• Mentor engineers and architects on AI engineering best practices
• Core Platforms Frameworks Tooling
• LLM and foundation model platforms e
• g
• AWS Bedrock Azure OpenAI Vertex AI
• Agentic AI and orchestration frameworks LangChain LangGraph CrewAI AutoGen Google ADK or equivalent
• Vector databases and search technologies OpenSearch Pinecone FAISS Weaviate
• Model lifecycle and deployment tooling Kubernetes containers serverless runtimes
• CI CD and MLOps tooling for AI pipelines GitHub Actions Azure DevOps Jenkins
• Observability and monitoring tooling for AI systems OpenTelemetry Prometheus Grafana
• Client Orientation Leadership
• Partner with product and engineering teams to identify AI opportunities and shape roadmaps
• Support client workshops RFPs and solution presentations
• Mentor engineers on AI ML Gen AI best practices and emerging technologies
• Translate complex AI concepts into business friendly narratives

Technical Requirements:

• 13 years of experience in software engineering with 3 years in AI with strong architecture ownership
• Proven experience designing and implementing enterprise scale AI engineering or MLOps platforms
• Strong hands on experience with LLMs prompt engineering RAG and agent frameworks
• Proficiency in Python AI frameworks and cloud native AI services
• Experience in Kubernetes CI CD and secure deployment of AI models
• Experience integrating AI capabilities into enterprise scale systems
• Good to Have Skills
• Experience with multi agent orchestration and autonomous workflows
• Knowledge of model observability and monitoring tooling
• Exposure to QE platforms test automation frameworks or AI assisted testing
• Domain experience in regulated industries such as BFSI Healthcare Telecom
• Cloud and AI certifications

Preferred Skills:

Technology->AI-AI Engineering->LLMOps,Technology->Artificial Intelligence->Artificial Intelligence - ALL,Technology->AI-Generative AI->Generative AI - Basic->model framework (langchain),Technology->Open System->Open System- ALL->Python,Technology->AI-AI Engineering->Model Deployment (Kubernetes),Technology->Agile Testing->Agile Testing - ALL->CD/CI,Technology->AI-Agentic AI->Agent Engineering,Technology->Architecture->Architecture - ALL