AI Engineering Architect

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 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.