<p><p><b>Role : Solutions Architect GenAI, AI/ML & AWS Cloud</b><br/><br/>Architect the Future of AI with goML<br/><br/>At goML, we design and build cutting-edge Generative AI, AI/ML, and Data Engineering solutions that help businesses unlock the full potential of their data, drive intelligent automation, and create transformative AI-powered experiences.<br/><br/> Our mission is to bridge the gap between state-of-the-art AI research and real-world enterprise applications - helping organizations innovate faster, make smarter decisions, and scale AI solutions seamlessly.<br/><br/>Were looking for a Solutions Architect with deep expertise in designing AI/ML and GenAI architectures on AWS.<br/><br/> In this role, youll be responsible for crafting scalable, high-performance, and cost-effective AI solutions - leveraging AWS AI/ML services, modern data infrastructure, and cloud-native best practices.<br/><br/> If you thrive in architecting intelligent, data-driven systems and love solving complex technical challenges, wed love to hear from you!<br/><br/><b>Why You?
Why Now ?</b><br/><br/>Generative AI is reshaping industries, and businesses are looking for scalable, cost-efficient, and production-ready AI/ML solutions.<br/><br/> This role is perfect for someone who loves solutioning AI/ML workloads, optimizing cloud infrastructure, and working directly with clients to drive real-world impact.<br/><br/>At goML, you will :</p><p> <br/>- Own the architecture and solutioning of AI/ML and GenAI applications<br/><br/></p><p>- Work with sales & engineering leaders to scope customer needs & build proposals<br/><br/></p><p>- Design scalable architectures using AWS services like SageMaker, Bedrock, Lambda, and Redshift<br/><br/></p><p>- Influence high-impact AI/ML decisions while working closely with the co-founders<br/><br/><b>What Youll Do (Key Responsibilities) 30 Days : Foundation & Orientation :</b></p><p><br/></p><p>- Deep dive into goMLs AI/ML & GenAI solutions, architecture frameworks, and customer engagements</p><p><br/><p>- Familiarize yourself with goML and AWS partnership workflows</p><p><br/>- Work alongside sales leaders to understand customer pain points & proposal workflows</p></p><br/>- Review and refine best practices for deploying AI/ML workloads on AWS<br/><br/>- Start contributing to solution architectures, and lead client discussions<br/><br/><b>First 60 Days : Execution & Impact : </b></p><p><b><br/></b></p><p>- Own customer AI/ML solutioning, including LLMOps, inference optimization, and MLOps pipelines<br/><br/>- Collaborate with engineering teams to develop reference architectures & POCs for AI -workloads<br/><br/>- Build strategies to optimize AI/ML model deployment, GPU utilization, and cost-efficiency in AWS<br/><br/>- Assist in sizing and optimizing AWS infrastructure for AI/ML-heavy workloads<br/><br/>- Work closely with customers to translate GenAI and AI/ML requirements into scalable architectures<br/><br/><b>First 180 Days : Ownership & Transformation : </b></p><p><br/></p><p>- Lead AI/ML architectural decisions for complex enterprise-scale AI projects<br/><br/>- Optimize multi-cloud and hybrid AI/ML deployments across AWS, Azure, and GCP<br/><br/>- Mentor team members on best practices for GenAI & cloud AI deployments<br/><br/>- Define long-term strategies for AI-driven data platforms, model lifecycle management, and cloud AI acceleration<br/><br/>Represent goML in technical conferences, blogs, and AI/ML meetups<br/><br/><b>What You Bring (Qualifications & Skills) : </b></p><br/>- 5 - 8 years of experience designing AI/ML and data-driven architectures on AWS<br/><br/>- At least 2 years of hands-on experience in GenAI, LLMOps, or advanced AI/ML workloads<br/><br/>- Deep expertise in AWS AI/ML services (SageMaker, Bedrock, Lambda, Inferentia, Trainium)<br/><br/>- Strong knowledge of AWS Data Services (S3, Redshift, Glue, Lake Formation, DynamoDB)<br/><br/>- Experience in optimizing AI/ML inference, GPU utilization, and MLOps pipelines<br/><br/>- Excellent client-facing communication skills with experience in proposal writing<br/><br/><b>Nice-to-Have : </b><br/><br/>- Familiarity with Azure ML, GCP Vertex AI, and NVIDIA AI/ML services<br/><br/>- Experience in LangChain, RAG architectures, and multi-modal AI models<br/><br/>- Knowledge of MLOps automation, CI/CD for AI models, and scaling inference workloads<br/></p><br/></p> (ref:hirist.tech)