Solution Architect

About the role

This role involves designing and guiding scalable software solutions, from individual components to enterprise platforms. The Lead Solution Architect will define architecture patterns, standards, and reusable frameworks, translating business requirements into secure technical solutions. A key part of the work is ensuring interoperability across various systems, data layers, and AI services within the organization.

The position requires developing and maintaining enterprise architecture roadmaps, aligning IT strategy with business goals, and establishing governance models. The architect will lead review boards and technical decision-making processes. A significant focus is on architecting and optimizing cloud-native and hybrid solutions using AWS, defining migration strategies, and implementing Infrastructure-as-Code.

A core responsibility is designing AI/ML infrastructure, pipelines, and integration patterns, including solutions incorporating LLMs and generative AI. This involves establishing AI governance frameworks for responsible AI usage, data privacy, and compliance, as well as setting up observability and monitoring capabilities for AI systems. The architect will also define and enforce agent governance and control mechanisms.

The salary for this role ranges from $50,000 to $80,000 USD.

Skills that matter here

• AWS: The role involves architecting and optimizing cloud-native and hybrid solutions using AWS services, defining cloud migration strategies, and ensuring cost optimization and performance.
• AI: This position requires designing AI/ML infrastructure, pipelines, and enterprise integration patterns, including solutions with LLMs and generative AI, and establishing AI governance frameworks.
• Microservices: The architect will design end-to-end architectures, including component-level services like microservices, and possesses strong knowledge of microservices and event-driven architectures.
• APIs: The role includes designing component-level services such as APIs and requires strong knowledge of API management.
• Infrastructure-as-Code: The architect will implement Infrastructure-as-Code and automation best practices within AWS cloud solutions.
• Data Governance: The role involves defining and implementing enterprise AI governance frameworks that cover data privacy, lineage, and compliance, as well as policies for data governance.

Who this role suits

• A person with 8-12+ years of experience in software engineering and architecture roles, specifically in designing large-scale distributed systems.
• Someone who can act as a strategic liaison across Semantic, Data, and ML architecture domains, facilitating alignment and providing guidance to specialized architects.
• An individual who can translate business requirements into scalable and secure technical solutions and ensure architectures meet enterprise security standards.
• A leader capable of mentoring architects and senior engineers, and acting as a trusted advisor to leadership and stakeholders.

From the employer

Architecture & Solution Design

• Design end-to-end architectures spanning:
• Component-level services (microservices, APIs)
• Domain platforms
• Enterprise-wide ecosystems
• Define architecture patterns, standards, and reusable frameworks
• Translate business requirements into scalable and secure technical solutions
• Ensure interoperability across systems, data layers, AI services, and platforms

Enterprise Architecture Strategy

• Develop and maintain enterprise architecture roadmaps
• Align IT strategy with business goals and digital transformation initiatives
• Establish governance models (TOGAF/SAFe or similar)
• Lead architecture review boards and technical decision-making processes

Cloud Architecture (AWS)

• Architect and optimize cloud-native and hybrid solutions using AWS services
• Define cloud migration strategies and modernization approaches
• Ensure high availability, resiliency, cost optimization, and performance
• Implement Infrastructure-as-Code and automation best practices

AI, Data & Intelligent Systems Architecture

• Design AI/ML infrastructure, pipelines, and enterprise integration patterns
• Architect solutions incorporating LLMs, generative AI, and intelligent agents
• Guide adoption of AI technologies within enterprise platforms and products
• Establish patterns for:
• RAG (Retrieval-Augmented Generation)
• Feature stores and data pipelines
• Model deployment, versioning, and scaling

AI Governance, Observability & Control

• Define and implement enterprise AI governance frameworks covering:
• Responsible AI usage (fairness, bias mitigation, explainability)
• Data privacy, lineage, and compliance
• AI risk classification and policy enforcement
• Establish AI observability and monitoring capabilities, including:
• End-to-end tracing of AI/ML and LLM flows using tools such as OpenTelemetry
• Monitoring of prompts, responses, latency, and model behavior using platforms like Langfuse or equivalent
• Metrics for model performance, drift, hallucination rates, and usage patterns
• Design and enforce agent governance and control mechanisms, including:
• Monitoring and auditing of autonomous and semi-autonomous AI agents
• Guardrails for agent behavior, tool usage, and decision boundaries
• Human-in-the-loop (HITL) workflows and escalation patterns
• Policy-based control over agent actions and integrations
• AI lifecycle governance, including:
• Model validation, approval workflows, and audit trails
• Continuous evaluation and feedback loops
• Secure model and prompt management

Cross-Disciplinary Architecture Leadership

• Act as a strategic liaison across Semantic, Data, and ML architecture domains
• Facilitate alignment between knowledge graphs, ontologies, data platforms, and ML systems
• Provide architectural guidance to specialized architects, ensuring cohesive enterprise integration
• Bridge gaps between business semantics, data engineering, and machine learning pipelines

Security, Compliance & Governance

• Ensure architectures meet enterprise security standards (e.g., Zero Trust)
• Define policies for data governance, access control, and auditability
• Align AI and cloud solutions with regulatory and compliance frameworks

Collaboration & Leadership

• Work with engineering, product, data, and AI teams to align solutions
• Mentor architects and senior engineers
• Act as a trusted advisor to leadership and stakeholders

Skills

Must have

• Core Architecture
• 8-12+ years in software engineering and architecture roles
• Proven experience designing large-scale distributed systems
• Strong knowledge of Microservices and event-driven architectures
• API management