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Data Architect - Agentic AI

Data Architect - Agentic AI

Spectrum ConsultingChennai
14 days ago
Job description

Job Title : AI Architect - Agentic Systems & Data Context

Location : Chennai

Job Type : Full-Time

Experience Level : 8+ years

Role Overview

As our AI Architect, you will be the chief designer of our intelligent, autonomous systems. You will establish the technical vision and architectural blueprint for Kripya's next-generation agentic AI solutions that power our hyper-automation platform. You will bridge the gap between our ambitious business goals and our engineering teams, making high-stakes technology decisions that will define our scalability, security, and competitive edge for years to come. This is a leadership role for a strategic thinker passionate about building robust, enterprise-grade AI solutions that solve complex data and context management challenges.

Key Responsibilities :

  • Strategic AI System Design : Translate complex business requirements into coherent, scalable, and secure technical blueprints for end-to-end AI solutions.
  • Agentic AI Architecture : Design and oversee the implementation of multi-agent AI architectures, defining agent roles, communication protocols, and orchestration workflows to solve complex business problems autonomously.
  • Data Context and Retrieval Architecture : Architect scalable solutions for managing AI context windows when processing large volumes of enterprise data, utilizing patterns like Retrieval-Augmented Generation (RAG) and knowledge graphs.
  • Technology Governance & Selection : Evaluate and select the optimal technologies, platforms, and frameworks for building agentic AI, including LLMs, vector databases, and data processing tools.
  • Ethical & Secure AI : Define and enforce governance frameworks for the ethical, secure, and compliant deployment of autonomous AI systems, addressing potential risks and ensuring model interpretability.
  • Technical Leadership & Mentorship : Provide architectural oversight and guidance to AI engineering teams, ensuring implementation aligns with the strategic technical vision.
  • Stakeholder Communication : Clearly articulate complex AI concepts, strategies, and architectural decisions to technical teams and non-technical business leaders to ensure alignment.

Required Qualifications

  • Experience : A minimum of 8 years in software engineering and system architecture, with a proven track record of designing and deploying large-scale AI / ML solutions.
  • Education : Bachelors degree in computer science, AI, or a related technical field.

    • Core Architecture Skills :

  • Proven experience designing scalable and resilient systems on cloud platforms (AWS, Azure, or GCP).
  • Deep architectural knowledge of microservices, event-driven systems, and containerization technologies (Docker, Kubernetes).
  • Proficiency in designing data storage patterns for AI systems using various SQL and NoSQL databases.

    • Data & Context Architecture Skills :

  • Demonstrable experience designing and implementing Retrieval-Augmented Generation (RAG) architectures to ground AI responses in enterprise data.
  • Proficiency in context engineering techniques for optimizing LLM performance with large datasets (e.g., context selection, summarization, and management).
  • Experience with knowledge graphs or semantic layers to provide structured, machine-readable context to AI systems.
  • Strong understanding of big data technologies (e.g., Spark, Kafka) for processing data at scale.

    • Agentic AI & ML Skills :

  • Experience designing agentic AI architectures, including single-agent and multi-agent systems.
  • Strong architectural understanding of LLMs and their application as reasoning engines in autonomous systems.
  • Familiarity with the principles of agentic frameworks (e.g., LangChain, AutoGen).
  • Architectural knowledge of the end-to-end MLOps lifecycle.

    • Leadership & Communication Skills :

  • Exceptional ability to translate business strategy into a technical roadmap.
  • Excellent communication skills, with the ability to influence and build consensus with technical and non-technical stakeholders.
  • Proven experience in mentoring and providing technical leadership to development teams.

    • Preferred Qualifications

  • Masters or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
  • Cloud certifications (e.g., AWS Certified Solutions Architect, Azure Solutions Architect Expert).
  • Published research or active contributions to open-source AI / ML projects.

    • (ref : hirist.tech)

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