| 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-tuning 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.
Preferred Qualifications - Experience with agent orchestration frameworks.
- Knowledge of machine learning and deep learning models beyond NLP.
- Exposure to data strategy at enterprise scale including cost-optimized LLM provisioning.
- Hands-on observability tools for monitoring AI systems.
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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 desi...
| 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-tuning 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.
Preferred Qualifications - Experience with agent orchestration frameworks.
- Knowledge of machine learning and deep learning models beyond NLP.
- Exposure to data strategy at enterprise scale including cost-optimized LLM provisioning.
- Hands-on observability tools for monitoring AI systems.
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Job Location:
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
