Senior AI / Agentic Architect

Comviva; Bengaluru; On-site; INR 2,000,000 - 3,500,000; Full time

Job summary

Comviva is seeking a highly experienced Senior AI/Agentic Architect to lead the architecture and engineering of their next-generation Agentic Orchestration Platform. The ideal candidate will possess over 12 years of experience and a strong background in agentic AI systems, multi-agent orchestration, and cloud-native platforms such as AWS, Azure, or GCP.

This role focuses on transforming traditional AI workflows into governed multi-agent systems capable of intelligent decision-making across various product platforms.

Qualifications

• 12+ years of experience in a relevant field.
• Strong coding experience in Python, FastAPI, and Node.js/TypeScript.
• Hands-on experience with cloud-native AI platforms.

Responsibilities

• Lead the architecture and engineering of Comviva’s Agentic Orchestration Platform.
• Define and architect enterprise-wide AI systems.
• Design scalable architectures for multi-agent orchestration and workflow automation.

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

AI memory frameworks

AI evaluation pipelines

Tools

AWS

Azure

GCP

Kubernetes

Docker

Microservices

Event-driven architectures

Kafka

API-first architectures

Terraform

Job description

Experience: 12+ Years

Location: Bengaluru

Function: Technology Unit – AI, Agentic AI & Platform Engineering

Role Summary

Looking for a highly experienced Senior AI / Agentic Architect to lead the architecture and engineering of Comviva’s next‑generation Agentic Orchestration Platform and Context Engineering Fabric. This role will drive the transition from traditional AI‑assisted workflows to autonomous yet governed multi‑agent systems capable of orchestrating decisions, workflows, product intelligence, and operational automation across product platforms including BSS, Fintech, Martech, CPaaS, and AI Ops ecosystems.

The Architect will work closely with Product Units, AI COE, Platform Engineering, Security, Performance Engineering, and Cloud Teams to establish a scalable, secure, telco‑grade AI platform that supports:

• Multi‑agent orchestration
• Context‑aware reasoning
• AI‑native workflows
• Human‑in‑the‑loop governance
• AI security and guardrails
• Real‑time operational intelligence
• Agent marketplace enablement
• SaaS and cloud‑native extensibility

Key Responsibilities

• Define and architect the enterprise‑wide Agentic Orchestration Platform for telecom‑grade AI systems.
• 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 approvals
  • Agent communication frameworks
• Design and implement autonomous agents, tool‑using agents, retrieval‑augmented generation (RAG), multi‑agent collaboration patterns, AI copilots, AI Ops agents, and decision intelligence systems.
• Define architecture standards for:
  • Prompt engineering
  • Context injection
  • Agent memory
  • Evaluation frameworks
  • AI observability
  • Hallucination mitigation
  • Responsible AI controls
• Architect cloud‑native AI platforms on AWS/Azure/GCP.
• Design scalable runtime infrastructure using Kubernetes, container orchestration, service mesh, API gateways, and event streaming frameworks.
• Drive platform engineering best practices for internal developer platforms (IDP), GitOps, infrastructure as code, AI workload scalability, GPU‑aware scheduling, and performance optimization.
• Define enterprise AI governance patterns for responsible AI, explainability, auditability, security guardrails, data privacy, and model access controls.

Required Skills & Experience

Core AI / Agentic 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 experience with LLM orchestration frameworks, RAG architectures, vector databases, AI memory frameworks, and AI evaluation pipelines.

Experience In One Or More

• LangChain
• LangGraph
• Semantic Kernel
• CrewAI
• AutoGen
• MCP (Model Context Protocol)
• AI Gateway frameworks
• Agent lifecycle frameworks
• AI observability platforms

Strong Expertise In

• AWS / Azure / GCP
• Kubernetes
• Docker
• Microservices
• Event‑driven architectures
• Kafka
• API‑first architectures
• Platform Engineering
• GitOps
• Terraform

Strong Coding Experience In

• Python
• FastAPI
• Node.js / TypeScript (preferred)
• Distributed systems engineering
• API integration frameworks