Solution Architect

Asurion; United States; Hybrid; USD 140,000 - 190,000; Full time

Job summary

Asurion is seeking a Solution Architect to provide technical leadership for complex, scalable systems and mentor engineers while aligning solutions with business outcomes.

Hybrid work in Sterling, VA or Nashville, TN with product, security, and operations collaboration to design resilient platforms and accelerate delivery.

Qualifications

• Experience delivering production systems and leading technical initiatives.
• Ability to design scalable, secure, resilient distributed systems.
• Strong understanding of AI/ML concepts and enterprise AI platforms.
• Familiarity with cloud-native architectures and security best practices.

Responsibilities

• Design end-to-end technical solutions aligned with objectives and standards.
• Provide technical leadership and mentor development teams.
• Evaluate technology options, architecture patterns, and third-party solutions.
• Drive architecture reviews, risk mitigation, and governance compliance.

Skills

Artificial Intelligence & ML

Agentic AI

Enterprise AI Platforms

Responsible AI

API & Integration Architecture

Cloud Architecture

Containerization

DevSecOps & CI/CD

Data Engineering

Security Engineering

Observability & Reliability

Full-Stack Solution Design

Education

Bachelor's degree in Computer Science or related field

Tools

Azure OpenAI

AWS

Google Vertex AI

Kubernetes

Docker

LangChain

Job description

Solution Architect

Location: hybrid in Sterling, VA or Nashville, TN

The Solutions Architect provides technical leadership for complex, scalable systems. This role drives architecture, code quality, and reliability across critical services while mentoring engineers and aligning solutions with business outcomes. The engineer partners with product, security, and operations to design resilient platforms, reduce risk, and accelerate delivery. Success requires hands-on development, thoughtful tradeoffs, and clear communication that advances engineering standards and unlocks team effectiveness.

Essential Job Skills/Duties

• Partner with business stakeholders, product managers, and engineering teams to understand business needs and translate them into scalable, secure, and maintainable solution architectures.
• Design end-to-end technical solutions that align with business objectives, enterprise architecture standards, and long-term platform strategy.
• Identify opportunities to leverage Artificial Intelligence (AI), Machine Learning (ML), automation, and Generative AI, and design AI-enabled solutions including AI workflows, LLMs, RAG, and AI agents where appropriate.
• Develop architecture artifacts including solution diagrams, integration designs, API specifications, data flows, and technical documentation.
• Evaluate technology options, architecture patterns, and third-party solutions, providing recommendations based on scalability, security, maintainability, cost, and business value.
• Design cloud-native, API-first, event-driven, and integration solutions that promote reuse, flexibility, and operational excellence.
• Collaborate with engineering teams throughout the software development lifecycle to ensure solutions are implemented in accordance with architectural designs and best practices.
• Participate in architecture reviews, identify technical risks, recommend mitigation strategies, and ensure compliance with enterprise architecture, security, and governance standards.
• Contribute to platform modernization, reusable architecture patterns, and continuous improvement initiatives while staying current on emerging technologies and AI advancements.
• Provide technical leadership and mentorship to development teams, fostering sound architectural practices, innovation, and cross-functional collaboration.

Required Technical Skills

• Artificial Intelligence & Machine Learning: Strong understanding of AI/ML concepts, including supervised and unsupervised learning, deep learning, Generative AI, Large Language Models (LLMs), embeddings, vector databases, Retrieval-Augmented Generation (RAG), prompt engineering, AI orchestration, model evaluation, and AI governance.
• Agentic AI & Intelligent Automation: Hands-on experience designing, building, and integrating AI-powered workflows, autonomous AI agents, and intelligent automation solutions using enterprise AI frameworks and orchestration platforms. Ability to identify business use cases where AI can optimize processes, improve customer experiences, and drive operational efficiency.
• Enterprise AI Platforms: Experience designing solutions using enterprise AI services such as Azure OpenAI, Amazon Bedrock, OpenAI, Anthropic Claude, Google Vertex AI, or equivalent platforms. Familiarity with AI frameworks such as LangChain, LangGraph, CrewAI, Semantic Kernel, AutoGen, or similar is preferred.
• Responsible AI & AI Security: Strong understanding of responsible AI principles, AI security, privacy, governance, model lifecycle management, regulatory compliance, and ethical AI practices.
• Application Architecture & Systems Design: Expertise in designing scalable, secure, resilient, and highly available distributed systems, including application decomposition, domain-driven design, integration patterns, and modern architectural styles such as microservices and event-driven architectures.
• API & Integration Architecture: Experience designing RESTful APIs, GraphQL, asynchronous messaging, event-driven integrations, and enterprise integration patterns to enable secure, scalable communication across platforms and services.
• Cloud Architecture: Experience designing and implementing cloud-native solutions on AWS, Azure, or Google Cloud, including serverless, containerized, and hybrid cloud architectures. Ability to design cloud-agnostic solutions using abstraction and portability patterns.
• Containerization & Orchestration: Experience designing and deploying containerized applications using Docker, Kubernetes, OpenShift, Amazon ECS/EKS, Azure AKS, or equivalent orchestration platforms.
• DevSecOps & CI/CD: Strong understanding of DevSecOps principles, infrastructure as code, automated testing, continuous integration, continuous delivery, release automation, feature management, observability, and deployment strategies.
• Application Packaging & Deployment: Experience packaging applications and services with required dependencies and configurations to support reliable, repeatable, and automated deployments across multiple environments.
• Software Engineering & Code Quality: Ability to review application architecture and source code to ensure adherence to engineering best practices, security standards, maintainability, performance, scalability, and coding standards.
• Data Engineering & Data Architecture: Experience designing modern data platforms, data pipelines, streaming architectures, data lakes, warehouses, and governance frameworks that support analytics, AI, and machine learning workloads.
• Full-Stack Solution Design: Understanding of modern application development across frontend, backend, APIs, databases, messaging, cloud infrastructure, and deployment pipelines to architect complete end-to-end business solutions.
• Security Engineering: Experience incorporating security-by-design principles into solution architecture, including identity and access management, encryption, secrets management, network security, vulnerability management, and zero-trust architecture.
• Observability & Reliability Engineering: Knowledge of monitoring, logging, tracing, performance engineering, resilience patterns, disaster recovery, and operational excellence to ensure highly reliable enterprise systems.

Required Soft / Leadership Skills

• Builds strong relationships and influences stakeholders across business and technology teams without direct authority to achieve aligned outcomes.
• Communicates complex business and technical concepts clearly and effectively to both technical and non-technical audiences, including executive leadership.
• Coaches and mentors engineers and peers by providing constructive feedback, sharing knowledge, and promoting architectural best practices.
• Balances immediate business priorities with long-term architectural sustainability, scalability, and maintainability when making technical decisions.
• Demonstrates sound judgment and collaborative decision-making by evaluating trade-offs, building consensus, and driving practical, business-focused solutions.

Required Education & Experience

• Bachelor’s degree in Computer Science or related field.
• 8+ years professional software engineering experience.
• Proven track record delivering production systems.
• Experience leading technical initiatives cross-team

Preferred Education & Experience

• Master’s degree in a relevant discipline.
• Experience in high-scale cloud environments.
• Prior impact as a Staff-level engineer.

Preferred Licenses/Certifications

• Cloud provider professional certification.
• Security certification such as CSSLP.

Supervisory Responsibilities

• Provides technical guidance and mentorship.
• Influences priorities without direct reports.