Solution Architect

About the role

In this role, the Lead Solution Architect will be responsible for designing and governing scalable software solutions that align with business strategies and security standards. The position emphasizes the use of AWS cloud technologies and advanced AI governance practices, ensuring that solutions are both effective and responsible.

The architect will work on a variety of projects, from component-level services to enterprise-wide ecosystems. Success in this role means effectively translating business requirements into secure technical solutions while collaborating with engineering, product, and AI teams to ensure cohesive integration across various domains.

The salary for this role ranges from $50,000 to $80,000 USD, reflecting the level of expertise required.

Skills that matter here

• AWS: This role requires the architect to design and optimize cloud-native solutions using AWS services.
• AI: The architect will guide the adoption of AI technologies within enterprise platforms.
• Microservices: Expertise in microservices is essential for designing scalable architectures.
• APIs: The role involves managing and designing APIs as part of the architecture.
• Infrastructure-as-Code: Implementing Infrastructure-as-Code is a key responsibility to ensure automation and best practices.
• Data Governance: Establishing data governance frameworks is crucial for compliance and security in AI solutions.

Who this role suits

• Has a background in software engineering and architecture with over 8 years of experience.
• Possesses strong leadership and mentoring skills to guide teams and influence stakeholders.
• Is comfortable working collaboratively across various technical domains and teams.
• Values responsible AI practices and is committed to ensuring compliance and security in solutions.

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