Solutions Architect - AI Platform

About Vericence

Vericence is a digital engineering and technology consulting firm helping enterprises build AI-driven platforms, modernize legacy systems, and scale innovation through cloud, data, and intelligent engineering. We partner with global organizations to deliver high-impact technology solutions and build world-class engineering teams.

Role Overview

We are building an AI-Native platform that autonomously ingests existing enterprise systems, user stories, and source code to deliver end-to-end software features with minimal human intervention. As Solution Architect, you will own the solution integrity of the entire platform, guiding a set of client stakeholders and internal stakeholders through valid deployment and implementation models for Context Graph, Event Orchestrator, Connectors, and Agent Development modules. You will be an expert in understanding SDLC and STLC lifecycles and can clearly come up with transformation levers for client implementations.

Key Responsibilities

• Define and own the end-to-end solution blueprint for the AI platform across all modules.
• Establish transformation guidelines, operating model standards, implementation approach, specific data and information needs for the platform.
• Lead solution reviews, drive trade-off decisions, and ensure alignment across module leads.
• Partner with the Principal Architect and Engineering Manager to translate product requirements into scalable solution strategy for clients.
• Provide feedback based on client implementations back to the platform and product teams.
• Oversee integration and implementation architecture between Client teams and Platform teams cutting across Context Graph, Event Orchestrator, Connectors, and Agent Development subsystems.
• Provide Solution and stakeholder mentorship to solution teams and product teams.
• Provide feedback on observability, security, and compliance standards for an AI-native SDLC platform.
• Engage with executive stakeholders to communicate roadmap direction and roadmap risks.
• Drive proof-of-concepts for emerging AI/ML capabilities and evaluate their production readiness.

Required Qualifications

• 15+ years of software engineering experience with at least 5 years in solution architect or transformational leader roles.
• Deep expertise in solutioning, designing, and transforming large-scale distributed systems, microservices, and event-driven architectures.
• Hands-on experience with LLM-based systems, RAG pipelines, knowledge graphs, or AI agent frameworks.
• Proficiency with cloud platforms (AWS, Azure, or GCP) and container orchestration (Kubernetes).
• Experience with graph databases (Neo4j, Amazon Neptune) and vector stores (Pinecone, Weaviate).
• Strong background in digital and technology transformation of large enterprise clients.
• Proven ability to lead solution architecture across multiple concurrent client engineering teams.
• Excellent written and verbal communication skills for both technical and executive audiences.
• Experience in Healthcare, Retail, or enterprise SaaS platform solution engineering is a strong plus.
• Familiarity with SDLC automation, Quality Engineering lifecycle, DevOps pipelines, and CI/CD best practices.

Preferred / Nice to Have

• Experience building platforms that integrate with Jira, GitHub, or enterprise ALM toolchains.
• Contributions to open-source AI/ML or agentic systems projects.
• Published solution frameworks or conference presentations in distributed systems or AI.