Senior AI / Agentic Architect
Comviva · Bengaluru
- Experience5–8 yrs
- SalaryNot disclosed
- Work modeonsite
- Posted1 Oct 2026
About Comviva
Comviva is hiring in Bengaluru in technology software. This role looks for around 5+ years of experience.
Skills
- Agentic AI systems
- Multi-agent orchestration
- AI workflow automation
- Context-aware AI architectures
- Generative AI platforms
- Autonomous systems design
- LLM orchestration frameworks
- RAG architectures
- Vector databases
- AI memory frameworks
- AI evaluation pipelines
- LangChain
- LangGraph
- Semantic Kernel
- CrewAI
- AutoGen
- Model Context Protocol
- AI Gateway frameworks
- Agent lifecycle frameworks
- AI observability platforms
- AWS
- Azure
- GCP
- Kubernetes
- Docker
- Microservices architecture
- Event-driven systems
- Kafka
- API-first design
- Platform engineering
- GitOps
- Terraform
- Python
- FastAPI
- Distributed systems engineering
- API integration frameworks
The role
An agentic AI architect at a technology software company designs Agentic AI systems and Generative AI platforms for enterprise orchestration, and builds RAG architectures, Kubernetes environments, and cloud-native AI platforms. Expertise spans Python, FastAPI, LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, AWS, Azure, GCP, Docker, Kafka, GitOps, and Terraform.
Full job description
Key Responsibilities
Define and architect enterprise-grade Agentic Orchestration Platforms Design scalable architectures for multi-agent orchestration, agent lifecycle management, agent memory and context handling, goal decomposition and planning, autonomous workflow execution, human-in-the-loop governance, and agent communication frameworks Design and implement autonomous and tool-using agents, Retrieval-Augmented Generation (RAG) systems, multi-agent collaboration patterns, AI copilots and decision intelligence systems, and AI Ops agents Establish architecture standards for prompt engineering, context injection, agent memory frameworks, AI evaluation and observability, hallucination mitigation, and responsible AI controls Architect cloud-native AI platforms on AWS, Azure, or GCP Design scalable runtime environments using Kubernetes, container orchestration, service mesh, API gateways, and event-driven frameworks Drive best practices for Internal Developer Platforms (IDP), GitOps & Infrastructure as Code, AI workload scalability, GPU-aware scheduling, and performance optimization Define enterprise-wide AI governance frameworks for responsible AI usage, explainability and auditability, data privacy and compliance, security guardrails, and model access control mechanisms
Required Skills
Strong experience in Agentic AI systems, multi-agent orchestration, AI workflow automation, context-aware AI architectures, generative AI platforms, and autonomous systems design Hands-on expertise in LLM orchestration frameworks, RAG architectures, vector databases, AI memory frameworks, and AI evaluation pipelines Experience with LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, Model Context Protocol (MCP), AI Gateway frameworks, agent lifecycle frameworks, and AI observability platforms Strong expertise in AWS / Azure / GCP, Kubernetes & Docker, microservices architecture, event-driven systems (Kafka, streaming platforms), API-first design, platform engineering, GitOps, and Terraform Strong coding experience in Python, FastAPI, Node.js / TypeScript (preferred), distributed systems engineering, and API integration frameworks
Key Competencies
Strategic thinking with hands-on architecture capability Strong problem-solving and system design skills Ability to work across cross-functional teams Deep understanding of scalable enterprise platforms Focus on innovation, governance, and performanc