Role : Principal Solution Architect Data & AI.
Location : Hyderabad, India (On-site).
Employment Type : Full-Time.
Experience : 7+ Years.
Industry : Technology / SaaS / Data Platforms / 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, and 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-efficient.
- 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, and business goals (growth, scalability, cost optimization, differentiation).
- Evaluate and guide trade-offs between speed vs scalability, cost vs performance, and flexibility vs complexity.
- Design systems that support long-term product evolution, monetization strategies, and AI-driven differentiation.
- AI AgentDriven 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, and Conversational assistants and natural language interfaces.
- Design agent orchestration frameworks, including multi-agent collaboration patterns, event-driven triggers and workflows, and context propagation across systems.
- Architect pipelines for data ingestion, feature extraction, model inference, and intelligent actions.
- Define integration patterns for LLMs and ML models, vector databases and embeddings, and real-time inference systems.
- Ensure explainability and observability of AI decisions, guardrails and fallback mechanisms, and 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, and 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 ProductArchitectureEngineering triad.
- Proactively identify and mitigate technical risks and 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, and scalable APIs and frontend systems.
- Architect data and AI pipelines, including streaming ingestion, feature engineering, and model inference layers.
- Work across technologies such as distributed systems and microservices architectures, SQL and NoSQL databases (MongoDB and Elasticsearch preferred), and modern web stacks (MERN or similar).
- Ensure efficient data flow across ingestion, processing, storage, and consumption layers.
- Forward-Looking Architecture :
- Partner with Product Managers to define long-term platform evolution.
- Drive transition toward AI-assisted systems, predictive insights, and autonomous workflows.
- Identify opportunities for platform extensibility, intelligent automation, and reusable AI-driven components.
- Build systems that are future-ready and 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, and 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), and 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, and vector databases, embeddings and semantic search.
- Experience or strong interest in building AI-powered and agent-based systems.
- Communication & Influence :
- Exceptional ability to explain complex systems in simple, business-friendly language and influence senior stakeholders and engineering teams.
- Strong written and verbal communication skills.
What Were Looking For
- A well-rounded solution architect who combines technical depth, product thinking, engineering alignment, and an AI-first mindset.
- Someone who can think like a customer, operate like a product partner, decide with the clarity of a senior architect, and operate effectively within a ProductArchitectureEngineering triad model.
Good To Have
- Background in observability, monitoring, or data platforms.
- Exposure to cloud-native architectures such as Microsoft Azure or 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 to Systems of Insight to Systems of Action.
- Work on cutting-edge challenges across distributed systems, data platforms, and AI and autonomous systems.
(ref:hirist.tech)
