KloudStax
Website:
kloudstax.com
Job details:
Position: AI/ML Engineering (Delivery)
Location: Remote (India)
Type: Full-Time
Compensation: ₹22,50,000 - ₹32,50,000 CTC
About KloudStax: KloudStax is one of the fastest-growing Google Cloud partners in the U.S., delivering modern cloud solutions that help organizations scale, innovate, and stay secure. As a Google Cloud Premier Partner, we help clients modernize infrastructure, migrate workloads, implement AI, build cloud-native applications, and optimize Google Cloud environments.
We're a remote-first engineering organization built around ownership, technical excellence, and solving complex business challenges. Our engineers work directly with clients, Google, and one another to deliver impactful solutions across AI, cloud infrastructure, security, data, and application modernization.
What You'll Do
AI Solution Architecture & Delivery
Design, build, and deploy production-grade AI solutions using Google Cloud.
Translate business requirements into scalable AI architectures leveraging Vertex AI, Gemini, Agent Builder, BigQuery, Cloud Run, GKE, and other Google Cloud services.
Design multi-agent workflows, Retrieval-Augmented Generation (RAG) systems, AI assistants, and enterprise search solutions.
Build secure, scalable, and maintainable AI applications that deliver measurable business value.
Application Development
Develop cloud-native applications integrating AI capabilities through APIs, microservices, and modern software engineering practices.
Build and maintain backend services supporting AI workloads using modern programming languages and frameworks.
Design integrations between enterprise systems, data platforms, and Google's AI ecosystem.
Develop reusable components, automation, and deployment frameworks that accelerate future client implementations.
Client Delivery
Partner directly with clients throughout discovery, architecture, implementation, testing, and production deployment.
Participate in technical workshops and architecture sessions to guide AI adoption strategies.
Build proofs of concept that demonstrate business value while establishing a clear path toward production deployment.
Support clients through implementation, optimization, and long-term adoption of AI technologies.
Engineering Excellence
Implement CI/CD pipelines, Infrastructure as Code, automated testing, and security best practices.
Collaborate with cross-functional engineering teams across cloud infrastructure, data engineering, and application development.
Stay current with Google's rapidly evolving AI platform and continuously evaluate new capabilities that can improve client outcomes.
Contribute reusable patterns, documentation, and internal best practices that improve delivery across the engineering organization.
What We're Looking For
Required Experience
3+ years of hands-on experience building solutions on Google Cloud Platform.
3+ years designing and implementing AI, Machine Learning, Generative AI, Agentic AI, or intelligent automation solutions.
Strong experience building production applications using Vertex AI, Gemini, and Google's AI platform.
Experience designing Retrieval-Augmented Generation (RAG), AI agents, conversational AI, enterprise search, or modern AI application architectures.
Experience working directly with clients in consulting, professional services, or client-facing engineering roles.
Experience working within distributed engineering teams using Agile methodologies.
Technical Expertise
Strong experience in several of the following: Google Cloud Platform, Vertex AI, Gemini, Agent Builder, BigQuery, Cloud Run, GKE (Kubernetes), Terraform / Infrastructure as Code, CI/CD pipelines, APIs & Microservices, Python (required), Java, Go, JavaScript/TypeScript, or similar languages, SQL and modern data platforms, Vector databases, Retrieval-Augmented Generation (RAG), Prompt engineering, AI model evaluation and optimization, Cloud security and IAM, and application modernization.
Required Qualifications
Google Cloud Professional Machine Learning Engineer Certification (required or actively pursuing prior to start date).
Bachelor's degree in Computer Science, Software Engineering, Data Science, or related technical discipline (or equivalent professional experience).
Excellent communication skills with the ability to explain complex technical concepts to both technical and business audiences.
Preferred Qualifications
Professional Cloud Architect
Professional Data Engineer
Professional Cloud Developer
Google Cloud Generative AI Leader Certification
Strong software engineering background with experience building production applications before moving into AI/ML.
Experience developing enterprise-grade APIs, backend systems, or cloud-native software products.
Experience with LangChain, LangGraph, CrewAI, Model Context Protocol (MCP), or similar orchestration frameworks.
Experience with Vertex AI Search, Agent Development Kit (ADK), Apigee, Firebase, AlloyDB, Cloud SQL, or other Google Cloud data platforms.
Experience delivering AI solutions within consulting or professional services organizations.
Experience mentoring engineers and contributing to technical leadership.
Click on Apply to know more.
