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Solutions Architect
1 month ago
Solution Architect (India)
Work Mode: Remote/ Hybrid
Required exp: 10+ years
Shift timing: Minimum 4 hours overlap required with US time
Role Summary:
The Solution Architect is responsible for designing robust, scalable, and high- performance AI and data-driven systems that align with enterprise goals. This role serves as a critical technical leaderbridging AI/ML, data engineering, ETL, cloud architecture, and application development. The ideal candidate will have deep experience across traditional and generative AI, including Retrieval- Augmented Generation (RAG) and agentic AI systems, along with strong fundamentals in data science, modern cloud platforms, and full-stack integration.
Key Responsibilities:
Design and own the end-to-end architecture of intelligent systems including data ingestion (ETL/ELT), transformation, storage, modeling, inferencing, and reporting.
Architect GenAI-powered applications using LLMs, vector databases, and RAG pipelines; Agentic Workflow, integrate with enterprise knowledge graphs and document repositories.
Lead the design and deployment of agentic AI systems that can plan, reason, and interact autonomously within business workflows.
Collaborate with cross-functional teams including data scientists, data engineers, MLOps, and frontend/backend developers to deliver scalable and maintainable solutions.
Define patterns and best practices for traditional ML and GenAI projects, covering model governance, explainability, reusability, and lifecycle management.
Ensure seamless integration of ML/AI systems via RESTful APIs with frontend interfaces (e.g., dashboards, portals) and backend systems (e.g., CRMs, ERPs).
Architect multi-cloud or hybrid cloud AI solutions, leveraging services from AWS, Azure, or GCP for scalable compute, storage, orchestration, and deployment.
Provide technical oversight for data pipelines (batch and real-time), data lakes, and ETL frameworks ensuring secure and governed data movement.
Conduct architecture reviews, mentor engineering teams, and drive design standards for AI/ML, data engineering, and software integration.
Qualifications:
Bachelors or Masters degree in Computer Science, Engineering, or a related field.
10+ years of experience in software architecture, including at least 4 years in AI/ML-focused roles.
Required Skills:
Expertise in machine learning (regression, classification, clustering), deep learning (CNNs, RNNs, transformers), and NLP.
Experience with Generative AI frameworks and services (e.g., OpenAI, LangChain, Azure OpenAI, Amazon Bedrock).
Strong hands-on Python skills, with experience in libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch.
Proficiency in RESTful API development and integration with frontend components (React, Angular, or similar is a plus).
Deep experience in ETL/ELT processes using tools like Apache Airflow, Azure Data Factory, or AWS Glue.
Strong knowledge of cloud-native architecture and AI/ML services on either one of the cloud AWS, Azure, or GCP.
Experience with vector databases (e.g., Pinecone, FAISS, Weaviate) and semantic search patterns. Experience in deploying and managing ML models with MLOps frameworks
(MLflow, Kubeflow).
Understanding of microservices architecture, API gateways, and container orchestration (Docker, Kubernetes).
Having forntend exp is good to have.
