Technical Architect - AI Platforms

Incedo Inc.

Gurugram District

On-site

INR 3,500,000 - 5,500,000

Full time

5 days ago
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Job summary

Incedo Inc. in Gurugram is seeking a Senior Enterprise Architect to define target architecture for AI-enabled enterprise platforms, services, APIs, data stores and security.

You will partner with Product and Engineering leadership, drive architecture governance, and influence client conversations with a strong emphasis on scalability, reliability and cost efficiency.

Qualifications

  • 12–16 years in software engineering, including 5+ years in solution or platform architecture.
  • Extensive experience with large-scale distributed systems and microservices.
  • Strong cloud architecture experience on Azure, AWS or GCP with Kubernetes.
  • Security by design, observability and cost-aware engineering practices.

Responsibilities

  • Define target architecture for enterprise AI platforms: services, APIs, data stores, security model and deployment topology.
  • Produce solution blueprints that engineering can build from and clients can reassure against.
  • Lead integration patterns, governance and architecture reviews across teams.

Skills

Large-scale distributed systems
Microservices and API architecture
Cloud architecture
DevSecOps fluency
Non-functional rigour
Architecture decision records

Education

TOGAF certification
Azure Solutions Architect Expert
AWS Solutions Architect Professional

Job description

You define end-to-end architecture for Incedo’s AI-powered enterprise products — applications, APIs, data, security and infrastructure — and you make it hold up across cloud, scale and audit.

You work directly with Product and engineering leadership, chair architecture governance, and act as the technical authority in high-stakes client conversations.

WHAT YOU'LL OWN
1. Architecture and blueprints
  • Define target architecture for enterprise AI platforms: services, APIs, data stores, security model, and deployment topology.
  • Produce solution blueprints that engineering can build from and that clients can assure against.
  • Design for scale, resilience and multi-tenancy across distributed, cloud-native systems.
  • Architect the AI layer — LLM and RAG serving, agent orchestration, vector stores, and the line between model-driven and deterministic behaviour.
  • Define AI infrastructure patterns: inference cost and latency, model routing, caching, evaluation hooks, observability.
  • Set the guardrail and data-handling architecture that makes AI deployable in regulated environments.
3. Integration and governance
  • Define integration patterns with enterprise platforms — identity, core systems, data pipelines, event backbones.
  • Lead architecture governance: review forums, standards, technical debt calls and architecture compliance across teams.
  • Drive technology evaluations, POCs and build-versus-buy calls on evidence rather than preference.
4. Engagement and influence
  • Partner with Product and Engineering leadership to keep architecture aligned to roadmap and delivery reality.
  • Represent the architecture to client CTOs, security teams and auditors, and support pre-sales and RFPs.
WHAT YOU'LL BRING
  • 12–16 years in software engineering, including 5+ years in solution or platform architecture.
  • Large-scale distributed systems designed and shipped — with the scars to show what fails at scale.
  • Deep microservices and API architecture: contracts, versioning and integration patterns.
  • Strong cloud architecture on Azure, AWS or GCP, with containerisation and Kubernetes in production.
  • DevSecOps fluency: security by design, secrets management, supply chain and CI/CD pipelines.
  • Non-functional rigour: performance, availability, observability, cost and compliance.
  • Decision discipline — able to write and defend an architecture decision record, not just a diagram.
GOOD TO HAVE
  • AI-powered enterprise applications architected and taken to production.
  • Hands-on exposure to LLMs, RAG, AI agents and GenAI platforms.
  • AI orchestration frameworks, vector databases and AI infrastructure design.
  • TOGAF, Azure Solutions Architect Expert or AWS Solutions Architect Professional certification.
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