TECHNICAL ARCHITECT AI

Position Overview We are seeking a highly skilled Technical Architect (AI) to join our this role you will leverage your expertise in Generative AI LLMs NLP and machine learning to design and implement innovative AI-driven solutions. The ideal candidate will have a deep understanding of architectural design RAG pipelines AI agents guardrails and the latest advancements in large language models. You will play a key role in delivering cutting-edge solutions working with large-scale data and building systems that enhance automation intelligence and efficiency for our clients. Key Responsibilities AI Solutioning & Architecture Lead the design and implementation of end-to-end AI solutions ensuring scalability, robustness and efficiency aligned with business needs. Architect RAG pipelines using frameworks like LangChain, LlamaIndex or custom-built stacks. Design Agentic AI architectures including task-based agents, stateful memory, planning-execution workflows and tool augmentation. Data Strategy & AI Model Development Define and execute data strategies for collection, cleaning, transformation and integration. Fine‑tuning & Prompt Engineering: Fine‑tune pre‑trained models (e.g. GPT, BERT etc.) and optimize prompt engineering techniques to drive high‑quality actionable outputs for diverse business use cases. Perform embeddings generation, evaluation of outputs and incorporate human/automated feedback loops. Apply advanced NLP techniques such as tokenization, prompt engineering and query optimization. Machine Learning & Deep Learning Models: Build, train and deploy machine learning models including deep learning models for complex AI applications across various domains. AI Guardrails & Safety Build and enforce guardrails for model safety and compliance including prompt validation, output moderation and access controls. Ensure solutions meet data governance, compliance and security standards. Deployment & Cloud‑Native Enablement Collaborate with teams to deploy solutions in AWS cloud‑native environments (Bedrock, Lambda, ECS, SageMaker, CDK). Oversee CI/CD pipelines, API integrations and scalable production deployments. Lead LLM provisioning from AWS balancing performance and cost‑effectiveness. Deployment & Evaluation: Oversee the deployment of AI models ensuring smooth integration with production systems and perform rigorous evaluation of LLMs for accuracy, efficiency and scalability. Observability & Post‑deployment Contribute to system observability. Support post‑deployment monitoring, optimization and retraining cycles for LLM‑driven systems. Technologies & Frameworks LLM: Expertise in AWS Bedrock RAG: LangChain, LlamaIndex, CrewAI, VectorDB Programming: Python Cloud Platforms: AWS (Bedrock, SageMaker, Lambda, CDK) Data & Databases: SQL, NoSQL, Data Lakes, Data Warehouses Orchestration & Deployment: CI/CD pipelines, containerized microservices, Kubernetes. Required Skills & Qualifications Proven production experience with RAG pipelines (LangChain, LlamaIndex or custom stacks). Strong understanding of Agentic AI patterns: task agents, memory/state tracking, orchestration. Expertise in LLM fine‑tuning, embeddings, evaluation strategies and feedback integration. Hands‑on experience with AI guardrails (moderation, filtering, prompt validation). Proficiency in Python, vector DBs and LLM APIs. Familiarity with CI/CD, API integration and cloud‑native deployments. Strong database management skills (SQL & NoSQL). Excellent communication, solutioning and leadership capabilities. Key Skills APIs, SOAP, Software Architecture, .NET, Design Patterns, Enterprise Software, AWS, Solution Architecture, Cloud Architecture, Java, SSO, Oracle Employment Details Employment Type: Full Time Experience: years Vacancy: 1 #J-18808-Ljbffr