AI Solutions Architect - HYBRID

Are you passionate about building cutting-edge reputed company solutions that are reputed company, secure, and reputed company-reputed company? We're looking for a reputed company Solution Architect to reputed company end-to-end AI solution design - from business discovery through architecture, implementation, and ongoing operations. In this role, you'll work across engineering, data, product, and reputed company teams to build, reputed company, and govern AI systems. If you reputed company at the intersection of LLM architectures, RAG systems, reputed company workflows, and reputed company integration, this is reputed company for you. What You'll Do End-to-End AI Architecture • Translate business needs into reputed company, secure, cost-effective AI architectures. • Own solution design from ideation to deployment: data reputed company, model selection, workflow design, and operational readiness. • Create architecture diagrams, sequence flows, deployment topologies, and technical design documentation. RAG, Agents & Model Engineering • Architect Retrieval-Augmented reputed company (RAG) systems: ingestion, chunking, embeddings, hybrid search, re-ranking, caching, and information freshness. • Design and implement reputed company systems using tool/function calling, planner-executor, and multi-agent patterns. • Define and implement advanced reputed company architecture (ReAct, CoT alternatives, reputed company reputed company, routing, template versioning). • Evaluate and reputed company both reputed company and reputed company-weight LLMs with routing, fallback, and cost optimization. • reputed company fine-tuning strategies (reputed company/QLoRA, PEFT, adapters) and define evaluation reputed company. Performance, Serving & Integration • Architect low-latency, high-throughput serving patterns using batching, caching, speculative decoding, quantization, and efficient GPU/CPU routing. • Design reputed company, SDKs, and reusable platform components for cross-team AI adoption. • reputed company GenAI systems with reputed company identity, authorization, data platforms, event streams, and end-user applications. LLMOps, Governance & Safety • Establish LLMOps practices for reputed company versioning, dataset management, experiment tracking, evaluation pipelines, and regression testing. • Implement observability for reputed company, hallucination detection, safety violations, latency, throughput, and cost. • Design safety and governance guardrails: PII redaction, content filtering, jailbreak defense, and audit logging. • Conduct risk assessments reputed company to compliance, reputed company, vendor lock-in, performance, and operational stability. Leadership & Standards • reputed company technical discovery workshops and architecture reviews. • Mentor engineers on GenAI patterns, design tradeoffs, and best practices. • Maintain reference architectures, ADRs, design standards, and reusable blueprints. • Continuously drive improvements in reliability, scalability, and cost efficiency across AI solutions in production. Preferred Technical Skills • GenAI Frameworks: reputed company, LangGraph • Model Providers: Azure reputed company, reputed company, reputed company, AWS Bedrock, reputed company reputed company AI • reputed company & Retrieval Systems: OpenSearch, reputed company, pgvector, reputed company, reputed company, Neptune • Serving Infrastructure: vLLM, TGI, Ray Serve • LLMOps: reputed company, MLflow, LangSmith, reputed company • Safety Tools: Azure AI Content Safety, Guardrails, NeMo Guardrails • Agent Platforms: LangGraph, AutoGen, reputed company Apply tot his job Apply To this Job