01Overview
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. Our mission is to bridge the gap between state-of-the-art AI research and real-world enterprise applicationshelping organizations innovate faster, make smarter decisions, and scale AI solutions seamlessly.
Were looking for a highly skilled Technical Architect with deep expertise in AWS, Generative AI, AI/ML, and scalable production-level architectures. In this role, youll lead end-to-end AI solution architecturefrom PoC to enterprise-scale production, drive cloud security and scalability best practices, and work closely with multiple clients and internal delivery teams. If you love architecting robust systems, mentoring engineering teams, and building GenAI solutions that actually shipwed love to hear from you.
That requires architects who can think beyond models and prototypessomeone who can design secure, scalable, multi-tenant AI solutions with clear MLOps foundations and cloud-native best practices.
owns architectures end-to-end (not just diagrams)
drives best practices in MLOps, DevOps, and cloud security
First 30 Days: Foundation & Architecture Alignment
Deep dive into goMLs GenAI/AI/ML delivery framework, reference architectures, and deployment standards
Review current AWS architecture patterns used across projects
Start contributing to solution planning, cloud design decisions, and technical estimation
Own the architecture of AI/ML and GenAI solutions end-to-end:
requirement analysis
cloud architecture design
implementation guidance
deployment readiness
Design multi-tenant, enterprise-grade AI systems using AWS services such as:
DevOps pipelines
Drive Conversational AI / RAG implementations:
vector search + hybrid retrieval
Collaborate closely with product, engineering, data science, and client teams through architecture reviews and workshops
First 180 Days: Ownership & Transformation
Lead full lifecycle AI architecturefrom PoC to productionwith reliability and performance focus
Design and guide implementation of:
event-driven architectures
serverless & microservices systems for AI workloads
security guardrails and monitoring
Own cost and performance optimization across AI workloads:
vector database tuning
ML engineers
Python developers
cloud engineers
go-to-market AI offerings
solution proposals and long-term innovation
912 years of overall experience, with strong background in technical architecture and cloud solutions
Proven experience designing and delivering production-grade AI/ML and GenAI applicationsStrong hands-on expertise across AWS services, especially:Deep knowledge of cloud-native architecture patterns:serverless architecturearchitecture walkthroughsExperience managing multiple client engagements or parallel deliveries
Experience with GraphQL API design and advanced enterprise integration patterns
Exposure to multi-cloud environments (AWS + Azure/GCP)
Strong background in building reusable frameworks/platform accelerators for GenAI delivery
Cloud, DevOps & Security
AWS: Bedrock, SageMaker, Lambda, API Gateway, DynamoDB, S3, ECS, Fargate, OpenSearch, RDS
MLOps/DevOps: SageMaker Pipelines, CI/CD (CodePipeline, GitHub Actions), Terraform, AWS CDK
AI/ML & Generative AI
Vector DBs: OpenSearch, Pinecone, FAISS
Architecture & Scalability
Serverless + microservices architectures
Performance optimization & autoscaling .
