Principal Solution Architect - Data, Azure & AI

Seosaph-infotech; Plano (TX); On-site; USD 180,000 - 260,000; Full time

Job summary

Seosaph-infotech is seeking a Principal Solution Architect to define and drive the architecture of a scalable, high-performance AI-native product platform. You will operate at the intersection of technology, product, business, and AI to ensure intelligent, adaptable systems.

You will shape AI-agent-driven design, establish governance, and lead cross-functional teams to align architecture with business goals and product roadmaps.

Qualifications

• AI/ML system design
• Explain complex systems in business terms
• Strong architectural decision making
• Cross-functional collaboration with product and engineering

Responsibilities

• 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.
• Partner with Product Managers to understand customer workflows and translate problems into architecture.
• Drive alignment with product roadmap and business goals through clear architectural decisions.

Job description

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

• 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:
• 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:
  • Flexibility vs complexity

Design systems that support:

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:
  • Event-driven triggers and workflows
  • Context propagation across systems
• 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
• 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:
  • Real-time and batch workflows
  • Scalable APIs and frontend systems
• Architect data and AI pipelines, including 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.
• 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
  • 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
• Ensure adherence to engineering and architectural standards across teams.

Required Skills & Qualifications

Domain Expertise

• ServiceNow
• CMDB
• DataOps
• PlatformOps
• FinOps

Technical Expertise

• 7+ years of experience in software engineering and architecture roles.
• 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 strong 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:

• Product thinking
• Engineering alignment

Someone who can:

• Think like a customer
• 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:
  • 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