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Posted 1 Oct 2026

GenAI Solution Architect / Principal Architect

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Employment
Full time
Posted
1 Oct 2026

About the role

Experience: 15+ Years
Location: Trivandrum
Employment Type: Full-Time

Job Summary

We are seeking a highly experienced GenAI Solution Architect to lead the design, development, and deployment of enterprise-scale AI Agent ecosystems. The ideal candidate will have deep expertise in multi-agent architectures, Generative AI frameworks, cloud-native solutions, and enterprise integrations. This role will be responsible for architecting intelligent agent-based solutions that enhance software engineering, testing, automation, and operational processes while ensuring security, governance, scalability, and cost optimization.

Key Responsibilities Multi-Agent Architecture & GenAI Solutions
  • Design and implement scalable multi-agent systems using frameworks such as LangChain, CrewAI, AutoGen, or similar agentic AI platforms.
  • Define architecture patterns for:
    • Agent orchestration
    • Memory management
    • Tool integration
    • Agent collaboration and delegation
    • Human-in-the-loop workflows
  • Build and deploy GenAI-powered agents for:
    • Requirement validation and automated correction
    • Test strategy and test scenario generation
    • Automation script generation and self-healing frameworks
    • Synthetic data generation
    • Performance planning and optimization
Enterprise Integration
  • Integrate AI agents with enterprise applications, workflow tools, and development ecosystems.
  • Enable seamless connectivity with:
    • CI/CD pipelines
    • DevOps platforms
    • ITSM tools
    • Observability and monitoring dashboards
    • Enterprise APIs and microservices
Security, Governance & Compliance
  • Implement robust AI governance frameworks and responsible AI practices.
  • Design and enforce:
    • Role-Based Access Control (RBAC)
    • Audit logging and traceability
    • Data privacy and security controls
    • AI guardrails and compliance mechanisms
  • Ensure alignment with enterprise security and regulatory requirements.
Performance & Cost Optimization
  • Optimize GenAI workloads for:
    • Token consumption reduction
    • Latency improvement
    • Cost efficiency
    • Scalability and performance
  • Implement advanced techniques such as:
    • Prompt engineering
    • Response caching
    • Context optimization
    • Model selection and routing strategies
Technical Leadership
  • Define GenAI architecture standards, best practices, and reusable frameworks.
  • Mentor architects, engineers, and product teams on:
    • Agentic AI design patterns
    • Prompt engineering
    • GenAI solution development
    • AI governance best practices
  • Drive innovation and evaluate emerging AI technologies and frameworks.
Required Skills & Qualifications Experience
  • 15+ years of overall IT experience with strong expertise in solution architecture and enterprise application development.
  • Proven experience designing and deploying enterprise-grade GenAI and AI Agent solutions.
Technical Skills
  • Hands-on experience with:
    • LangChain
    • CrewAI
    • Agentic AI frameworks
    • LLM integration and orchestration
  • Strong programming expertise in:
    • Python
    • TypeScript/JavaScript
  • Experience with REST APIs, SDKs, and third-party integrations.
Cloud & Platform Expertise
  • Strong understanding of cloud-native architectures.
  • Hands-on experience with:
    • AWS, Azure, or GCP
    • Docker
    • Kubernetes
    • Microservices architecture
    • Serverless technologies
Data & AI Technologies
  • Experience working with:
    • Vector databases such as Pinecone, PGVector, Weaviate, or ChromaDB
    • Retrieval-Augmented Generation (RAG)
    • Hybrid RAG architectures
    • Embedding models and knowledge retrieval systems
Security & Governance
  • Deep understanding of:
    • RBAC models
    • Enterprise security frameworks
    • Authentication and authorization mechanisms
    • Compliance and governance standards
Preferred Qualifications
  • Experience in AI-driven Software Development Lifecycle (SDLC) transformation.
  • Exposure to MLOps, LLMOps, and AI observability platforms.
  • Relevant cloud certifications (AWS Solutions Architect, Azure Architect, GCP Professional Architect).
  • Experience implementing Responsible AI frameworks and governance models.
  • Strong stakeholder management and executive communication skills.
Key Competencies
  • Strategic Thinking
  • Enterprise Architecture
  • AI Solution Design
  • Innovation & Problem Solving
  • Technical Leadership
  • Stakeholder Management
  • Mentoring & Coaching
  • Cost and Performance Optimization

Experience Required: 15+ Years
Role Level: Principal Architect / Senior Solution Architect
Domain: Generative AI, Agentic AI, Enterprise Architecture, Cloud-Native Platforms, Intelligent Automation.

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