Solution Architect - RAG / Agentic AI

Shift timing : Minimum 4 hours overlap required with US time

Job Description

A fast-growing, US private equitybacked AI company making significant headway in both the US and India markets. The company is focused on delivering outcome-focused digital experiencesfrom mobile and web to cloud and AI for enterprise clients worldwide. Be part of a growth oriented and well-funded AI company as it expands globally.

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 leader bridging 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 :

Required Skills :

(ref : hirist.tech)