AI Solution Architect

Cinergy Technology Inc; Hyderabad; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Cinergy Technology Inc. is seeking an experienced AI Solution Architect to design and lead scalable, secure production-ready AI architectures across AWS, Azure, and Google Cloud.

You will collaborate with business stakeholders, product managers, data scientists, ML engineers, software engineers, and cloud teams to translate requirements into enterprise-grade solutions. You will define patterns for AI applications, data platforms, APIs, microservices, and data pipelines; govern AI safety,

Qualifications

• 8+ years of experience in software, cloud, data, or solution architecture.
• Strong hands-on understanding of AI/ML and Generative AI technologies.
• Experience with AWS, Azure, or Google Cloud and enterprise-scale data platforms.

Responsibilities

• Design end-to-end AI architectures for AI/ML, GenAI, and LLM-based solutions.
• Define integration patterns between AI services and enterprise apps.
• Provide technical leadership during development, testing, deployment, and production.
• Establish standards for scalability, performance, security, and maintainability.
• Review designs, APIs, infrastructure, and AI/ML implementation approaches.
• Support MLOps and CI/CD architecture for model development and deployment.

Skills

8+ years exp

AI/ML knowledge

LLMs & RAG

Python

APIs & microservices

Cloud architecture

Security & IAM

Architecture docs

Education

AWS Solutions Architect

Azure Solutions Architect

Google Cloud Architect

Tools

Docker

Kubernetes

CI/CD

Infrastructure automation

Vector databases

Job description

We are looking for an experienced AI Solution Architect to design and lead the architecture of scalable, secure, and production-ready AI solutions. The candidate will work with business stakeholders, product managers, data scientists, AI/ML engineers, software engineers, and cloud teams to transform business requirements into enterprise-grade AI architectures.

Key Responsibilities

• Design end-to-end architectures for AI, Machine Learning, Generative AI, and LLM-based solutions.
• Analyze business and technical requirements and translate them into scalable solution architectures.
• Define architecture patterns for AI applications, data platforms, APIs, microservices, and cloud infrastructure.
• Design enterprise Generative AI and LLM solutions, including RAG, vector databases, embeddings, prompt engineering, and model integration.
• Evaluate and recommend appropriate AI/ML models, frameworks, platforms, and technologies.
• Design data pipelines and integration architectures required for AI solutions.
• Define integration patterns between AI services and existing enterprise applications.
• Collaborate with engineering and data teams to ensure architecture feasibility and implementation.
• Establish standards for scalability, performance, availability, security, and maintainability.
• Design AI solutions across cloud platforms such as AWS, Azure, and Google Cloud.
• Provide technical leadership during development, testing, deployment, and production implementation.
• Review technical designs, code architecture, APIs, infrastructure, and AI/ML implementation approaches.
• Support MLOps and CI/CD architecture for model development and deployment.
• Define AI governance, security, privacy, compliance, and responsible AI considerations.
• Conduct technical assessments, proof-of-concepts, and architecture reviews.
• Identify technical risks, dependencies, bottlenecks, and opportunities for optimization.
• Create architecture diagrams, technical specifications, solution proposals, and documentation.
• Communicate complex technical concepts to both technical and business stakeholders.

Required Skills

• 8+ years of experience in software, cloud, data, or solution architecture.
• Strong hands-on understanding of AI/ML and Generative AI technologies.
• Strong knowledge of LLMs, RAG, embeddings, vector databases, prompt engineering, and AI application architecture.
• Experience with Python and AI/ML frameworks.
• Strong knowledge of APIs, microservices, distributed systems, and cloud architecture.
• Experience with AWS, Azure, or Google Cloud.
• Understanding of data engineering, data lakes, databases, and data integration.
• Knowledge of MLOps, CI/CD, Docker, Kubernetes, and infrastructure automation.
• Strong understanding of security, identity, access management, and enterprise architecture.
• Excellent architecture documentation and communication skills.

Preferred Qualifications

• Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent platforms.
• Experience with vector databases such as Pinecone, Weaviate, Milvus, or Azure AI Search.
• Experience implementing enterprise RAG and agentic AI solutions.
• Knowledge of AI model evaluation, observability, governance, and responsible AI.
• Cloud architecture certification such as AWS Solutions Architect, Azure Solutions Architect, or Google Cloud Architect.
• Experience working with enterprise clients and large-scale production environments.

Soft Skills

• Strong technical leadership and architectural decision-making.
• Excellent communication and presentation skills.
• Strong analytical and problem-solving capabilities.
• Ability to work with both business and technical stakeholders.
• Ability to translate complex business requirements into practical technical solutions.