Role: Principal Solution Architect - Data & AI

? Location: Hybrid/On-site (Hyderabad)

? Employment Type: Full-Time

? Experience: 7+ Years

? Industry: Technology / SaaS / Data Platforms / Azure / AI

About the Role

We are looking for a highly experienced Principal Solution Architect to define and drive the architecture of a scalable, high-performance, AI-native product platform .

This role goes beyond traditional system design. You will operate at the intersection of technology, product, business, and AI , ensuring that systems are not only scalable and resilient but also intelligent, adaptive, and future-ready .

You will play a critical role in shaping:

- What we build
- Why we build it
- How it evolves into an AI-augmented / AI-agent-driven platform

Working closely with Product Managers, you will bring strong technical depth along with a forward-looking architectural vision , enabling the transition from deterministic systems to intelligent, agent-driven systems .

Key Responsibilities

Architecture Leadership

- Own the end-to-end architecture of the product platform across backend, data, and frontend layers.
- Define systems that are scalable, resilient, extensible, and cost-effective .
- Establish architectural principles, standards, and best practices across teams.
- Introduce patterns for AI-native system design , including agent orchestration and inference pipelines.

Customer-Centric Thinking

- Partner with Product Managers to deeply understand customer workflows, pain points, and usage patterns.
- Translate customer problems into architecture for:

-- Faster decision-making -- Reduced operational friction

-- Improved user outcomes

- Communicate technical decisions in clear business terms.

Business-Aligned Architecture

- Ensure all architectural decisions align with:

-- Product strategy and roadmap -- Business goals (growth, scalability, cost optimization, differentiation)
- Evaluate and guide trade-offs between:

-- Speed vs scalability -- Cost vs performance

-- Flexibility vs complexity

- Design systems that support:

-- Long-term product evolution -- Monetization strategies

-- AI-driven differentiation

AI Agent–Driven Architecture (Core Focus)

- Define architecture for AI agents embedded within the platform , such as:

-- Root Cause Analysis agents -- Anomaly detection agents

-- Incident response and remediation agents

-- Conversational assistants and natural language interfaces

- Design agent orchestration frameworks , including:

-- Multi-agent collaboration patterns -- Event-driven triggers and workflows

-- Context propagation across systems

- Architect pipelines for:





-- Data ingestion --> Feature extraction --> Model inference --> Intelligent actions
- Define integration patterns for:

-- LLMs and ML models -- Vector databases and embeddings

-- Real-time inference systems

- Ensure:

-- Explainability and observability of AI decisions -- Guardrails and fallback mechanisms

-- Human override workflows

- Balance deterministic systems with probabilistic AI behaviors.

Strong Point of View & Decision Making

- Bring clear, well-reasoned architectural opinions to discussions.
- Challenge ideas with both technical depth and business context .
- Confidently accept or reject approaches with structured justification around:

-- Technical feasibility and scalability -- Long-term maintainability

-- Business impact and ROI

-- AI model reliability and risk considerations

- Drive alignment across stakeholders with clarity and conviction .

Cross-Functional Leadership & Continuous Alignment

- Collaborate closely with Product Managers to stay aligned with the product roadmap, priorities and evolving business goals.
- Provide early architectural input during feature ideation and roadmap planning .
- Ensure architecture evolves in sync with roadmap changes, avoiding rework and misalignment .
- Guide Engineering teams with clear architectural direction while balancing short-term delivery and long-term vision.
- Act as a core partner in the Product–Architecture–Engineering triad .
- Proactively identify and mitigate:

-- Technical risks -- AI/ML risks including bias, drift, and reliability concerns

System Design & Technical Depth

- Design and evolve systems handling:

-- High-volume data processing -- Real-time and batch workflows

-- Scalable APIs and frontend systems

- Architect data and AI pipelines , including:

-- Streaming ingestion -- Feature engineering

-- Model inference layers

- Work across technologies such as:

-- Distributed systems and microservices architectures -- SQL and NoSQL databases (MongoDB and Elasticsearch preferred

-- Modern web stacks ( MERN or similar)

- Ensure efficient data flow across ingestion --> processing --> storage --> consumption layers .

Forward-Looking Architecture

- Partner with Product Managers to define long-term platform evolution.
- Drive transition toward:





-- AI-assisted systems -- Predictive insights

-- Autonomous workflows

- Identify opportunities for:

-- Platform extensibility -- Intelligent automation

-- Reusable AI-driven components

- Build systems that are:

-- Future-ready -- Adaptable to rapid AI advancements

Governance & Execution Excellence

- Create High-Level Designs (HLDs) and review and approve Low-Level Designs (LLDs).
- Drive design reviews, benchmarking, and capacity planning.
- Establish governance for:

-- Performance -- Reliability

-- Security

- AI model lifecycle management (versioning, evaluation, monitoring)
- Ensure adherence to engineering and architectural standards across teams.

Required Skills & Qualifications

Domain Expertise

- ServiceNow
- CMDB
- Database Architectures & Tools
- DataOps
- PlatformOps
- FinOps
- Application Architecture
- AI Architecture

Technical Expertise

- 7+ years of experience in software engineering and architecture roles.
- Strong experience designing scalable distributed systems .
- Hands-on expertise in:

-- Backend systems and APIs (Node.js and similar) -- Data platforms (SQL and NoSQL databases, MongoDB, Elasticsearch, Azure Data Platforms)

-- Modern frontend architectures (React or similar)

AI & Data Systems

- Strong understanding of:

-- AI/ML system design. (LLMs, Anomaly detection systems, Recommendation systems) -- Real-time inference pipelines and Batch ML workflows

-- Vector databases, embeddings and semantic search

- Experience or solid interest in building AI-powered and agent-based systems .

Communication & Influence

- Exceptional ability to:

-- Explain complex systems in simple, business-friendly language -- Influence senior stakeholders and engineering teams

- Strong written and verbal communication skills.

What We’re Looking For A well-rounded solution architect who combines:

- Technical depth
- Product thinking
- Engineering alignment
- AI-first mindset

Someone who can:
- Think like a customer
- Operate like a product partner
- Decide with the clarity of a senior architect
- Operate effectively within a Product–Architecture–Engineering triad model

Good to Have

- Background in observability, monitoring, or data platforms .
- Exposure to cloud-native architectures such as:
- Microsoft Azure
- Amazon Web Services (AWS)

Why This Role is Exciting

- Opportunity to architect a next-generation AI-native platform .
- Lead the shift from:

-- Systems of Record → Systems of Insight → Systems of Action
- Work on cutting-edge challenges across:

-- Distributed systems -- Data platforms

-- AI and autonomous systems

📌 Principal Solution Architect - Data, Azure & AI (Hyderabad)
🏢 Seosaph-infotech
📍 Hyderabad