3 Genai Architect Jobs

Job Title: GenAI Architect Experience Required: 10+ years in software architecture or machine learning roles, including at least 2+ years focused on Generative AI or Large Language Models (LLMs). Role Overview We are seeking a GenAI Architect to lead the design, development, and deployment of cutting-edge Generative AI solutions. This role requires deep expertise in LLMs, advanced AI architectures, and the ability to build scalable and production-ready systems leveraging the latest in AI technologies. Key Responsibilities Architect and implement GenAI solutions, including LLMs, RAG pipelines, embedding models, and vector search . Design and optimize prompt engineering strategies, fine-tuning approaches , and mitigate hallucinations in AI outputs. Develop robust AI workflows using Python, LangChain, Hugging Face Transformers , and vector databases such as Pinecone or Weaviate . Integrate and leverage GenAI APIs (OpenAI, Azure OpenAI, Anthropic, Google Vertex AI). Deploy AI applications in cloud-native environments (AWS, GCP, Azure) using Kubernetes and containerized architectures . Lead model evaluation, performance tuning, and ensure scalable architecture for enterprise use cases. Collaborate with business stakeholders to translate complex AI concepts into actionable solutions and value-driven outcomes. Required Skills & Qualifications 10+ years of experience in software architecture or machine learning, with 2+ years in GenAI/LLM-focused roles . Strong expertise in: LLMs and RAG pipelines Prompt engineering, fine-tuning, and hallucination mitigation LangChain, Hugging Face Transformers, Python Vector databases (Pinecone, Weaviate, etc.) Proficiency in deploying solutions on AWS/GCP/Azure with Kubernetes. Experience with model evaluation frameworks and industry best practices. Ability to communicate AI strategies and outcomes to non-technical stakeholders. Preferred Qualifications Hands-on experience with LLMOps tools (Weights & Biases, MLflow, Trulens, PromptLayer). Knowledge of domain-specific AI applications (real estate, finance, risk modeling). Exposure to multi-modal GenAI (text, image, document, voice). Contributions to open-source projects, research publications, or patents in AI/ML.

Job Title: GenAI Architect Experience Required: 10+ years in software architecture or machine learning roles, including at least 2+ years focused on Generative AI or Large Language Models (LLMs). Role Overview We are seeking a GenAI Architect to lead the design, development, and deployment of cutting-edge Generative AI solutions. This role requires deep expertise in LLMs, advanced AI architectures, and the ability to build scalable and production-ready systems leveraging the latest in AI technologies. Key Responsibilities Architect and implement GenAI solutions, including LLMs, RAG pipelines, embedding models, and vector search . Design and optimize prompt engineering strategies, fine-tuning approaches , and mitigate hallucinations in AI outputs. Develop robust AI workflows using Python, LangChain, Hugging Face Transformers , and vector databases such as Pinecone or Weaviate . Integrate and leverage GenAI APIs (OpenAI, Azure OpenAI, Anthropic, Google Vertex AI). Deploy AI applications in cloud-native environments (AWS, GCP, Azure) using Kubernetes and containerized architectures . Lead model evaluation, performance tuning, and ensure scalable architecture for enterprise use cases. Collaborate with business stakeholders to translate complex AI concepts into actionable solutions and value-driven outcomes. Required Skills & Qualifications 10+ years of experience in software architecture or machine learning, with 2+ years in GenAI/LLM-focused roles . Strong expertise in: LLMs and RAG pipelines Prompt engineering, fine-tuning, and hallucination mitigation LangChain, Hugging Face Transformers, Python Vector databases (Pinecone, Weaviate, etc.) Proficiency in deploying solutions on AWS/GCP/Azure with Kubernetes. Experience with model evaluation frameworks and industry best practices. Ability to communicate AI strategies and outcomes to non-technical stakeholders. Preferred Qualifications Hands-on experience with LLMOps tools (Weights & Biases, MLflow, Trulens, PromptLayer). Knowledge of domain-specific AI applications (real estate, finance, risk modeling). Exposure to multi-modal GenAI (text, image, document, voice). Contributions to open-source projects, research publications, or patents in AI/ML.

About this role: We are seeking a result-driven AI ML Platform Manager with a strong background in cloud technologies ( AWS, Azure) to lead the strategic development and delivery of enterprise-grade AI/ML platforms. This role is pivotal in enabling scalable, secure, and resilient business applications, integrating cloud-based systems, and driving digital transformation initiatives. This role will lead teams to achieve performance objectives and provide deep insights into best practices for solving complex problems. Role & responsibilities Lead an platform org of Cloud Administrators, Support Engineers, GenAI Ops Engineers and GenAI architects Collaborate with business unit heads, PMOs, and product managers to translate requirements into reliable platform capabilities Leading engagement delivery and managing client relationships on daily basis Standardize platform services across cloud and on-prem environments, ensuring alignment with enterprise architecture Accountable for program/project management and engagement economics Implement cost optimization and performance tuning for cloud workloads Lead cross-functional teams in developing APIs, integrations, and microservices that support data flow across systems Ensure robust CI/CD pipelines and infrastructure as code (IaC) using tools like Terraform or CloudFormation Implement observability tools (e.g., Fiddler, Datadog, Prometheus, Splunk) across enterprise workloads Enforce zero trust principles, encryption standards, and cloud security baselines Strong knowledge on micro-services deployment architecture with K8S experience Preferred candidate profile Bachelor's/Masters in Computer Science, Engineering, or related discipline 10+ years of experience in enterprise platform tools with 4 years of strong AI ML platform experience and 6+ years of cloud experience Proven experience in managing infrastructure and workloads on AWS, Azure, or GCP Proven experience in budget management, team management and cross functional operation. Strong communication and stakeholder management skills, with the ability to collaborate effectively across diverse teams and functions