GenAI Solutions Architect — Data, Apps & Enterprise AI

Lynx Analytics

Philadelphia (Philadelphia County)

On-site

USD 140,000 - 180,000

Full time

11 days ago

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Job summary

Lynx Analytics is seeking a Solution Architect to design the technical solutions behind client engagements across enterprise data, software applications and GenAI. You will translate business problems into practical architectures and provide a clear path from concept to production.

This hands-on, architecture-first role stays close to implementation and helps shape reusable patterns and standards for Lynx's AI-native life sciences practice while collaborating with delivery teams and clients.

Qualifications

Bachelor's degree in Computer Science, Engineering or a related field or equivalent practical experience.
5-8+ years of experience across data engineering, software engineering and solution or systems architecture.
Track record of designing data models, system architectures and integration patterns for production systems, not just diagrams.
Hands-on proficiency in Python or TypeScript and ability to prototype components.
Strong data engineering fundamentals: pipeline design, data modeling and ETL/ELT.
Strong software engineering fundamentals including API design, testing, security and CI/CD.
Hands-on experience designing or prototyping LLM-powered applications and GenAI architectures.
Experience with GenAI architecture patterns, embeddings, vector search, tooling calls and observability.
Experience integrating AI apps with enterprise data sources and workflows.
Experience with AWS, Azure or GCP.
Consulting or client-facing experience with discovery conversations and trade-offs.
Experience in life sciences or regulated industries is a strong advantage.

Responsibilities

Own the end-to-end solution architecture for client engagements, including data models, system design, integration patterns and technology choices.
Translate business requirements into clear technical designs and implementation paths for delivery teams.
Design solutions spanning enterprise data, APIs, applications, cloud platforms and GenAI capabilities.
Lead technical discovery with clients: understand requirements, assess systems and identify risks.
Present architectural options and trade-offs to technical teams and leaders.
Make pragmatic decisions on build speed, cost, scalability, security and maintainability.
Review key implementation decisions and stay involved through delivery to ensure alignment.