Solutions Architect

Aegistech; Jersey City (NJ); Hybrid; USD 140,000 - 220,000; Full time

Job summary

Aegistech is seeking a hands-on AI Solutions Architecture consultant for a Northern NJ based project. The role is hybrid onsite, three days a week, and requires U.S. work authorization as a W-2 employee with no relocation.

Responsibilities include leading architecture for ES platforms, identifying AI-enabled value, and guiding secure, observable, scalable implementations. Preferred experience includes AWS AI services and MCP integrations in regulated environments.

Qualifications

• 7+ years in software, platform, integration, or solutions architecture with hands-on production engineering and leadership.
• Applied AI solution design: LLM workflows, retrieval, tool/agent integration, quality evaluation.
• Enterprise service integration: Cloud architecture, REST APIs, identity, ops tooling, reusable patterns.
• Security and service reliability: data protection, observability, auditability, governance and production readiness.

Responsibilities

• Lead hands-on solution architecture for ES platforms and managed services.
• Define use cases, assess feasibility, value, cost, risk, and reuse before recommendations.
• Architect AI-enabled capabilities across cloud, identity, APIs, integration, and observability.
• Design for secure, operable services with runbooks, incident response, and rollback.
• Mentor engineers and coordinate delivery with BU tech teams and Security.

Skills

AI/ML design

Cloud architecture

REST APIs

Security & observability

Python/TypeScript

Cross-functional leadership

Tools

AWS AI services

Claude

Kong Konnect AI/MCP

Splunk/CloudWatch

Job description

Our client in Northern NJ is seeking a hands-on AI Solutions Architecture consultant. This position is hybrid onsite in Northern NJ 3 days a week in the office.

Local Candidates only/NO Relocation

This role is NOT eligible for employer-sponsored work authorization (e.g., H-1B, OPT, CPT, etc.) or transfer. Candidates must have valid U.S. work authorization. Candidate must work as our W-2 employee, no sub-contractors.

Purpose of the Role

Lead hands on solution architecture for Engineering Services (ES) platforms and managed business services. Partner with service owners and customers to identify where AI or simpler automation adds value, then guide design, engineering, and reliable operation of those capabilities.

Specific Responsibilities

• Partner with ES service owners, Technical Operations, and BU stakeholders to understand service requirements, operational friction, and customer outcomes; assess where AI is appropriate.
• Define use cases and success criteria; assess feasibility, value, cost, risk, and reuse before recommending experiments or enhancements to existing and new ES services.

Service Architecture and Engineering

• Architect AI enabled capabilities within ES cloud, identity, API/MCP, integration, connectivity, and observability services; apply secure, reusable enterprise patterns.
• Lead hands on evaluations and prototypes; guide solution development and integration through production readiness, with clear engineering acceptance criteria.

Managed Service Lifecycle and Quality

• Design for secure, supportable operations with service engineering and Technical Operations: evaluation, telemetry, access controls, runbooks, incident response, and rollback.
• Present evidence based options to ES and BU leaders, explaining service value, reliability, AI quality, cost, privacy, and human oversight tradeoffs.

Technical Leadership and Partnerships

• Lead cross functional architecture reviews and mentor engineers; coordinate solution delivery with BU technical teams, Security, and CIO Analytics on dependent applications and integrations.
• Translate architecture into demonstrable outcomes, communicate delivery risks, and maintain clear service and platform accountability.

Requirements

Required Experience

• 7+ years in software, platform, integration, or solutions architecture roles, with hands on production engineering, technical leadership, and service provider or customer facing experience.
• Applied AI solution design: LLM workflows, retrieval when appropriate, tool/agent integration, quality evaluation, model selection tradeoffs, and non AI alternatives.
• Enterprise service integration: Cloud architecture, REST APIs, MCP, identity and authorization, operations tooling, and reusable platform and service patterns.
• Security and service reliability: Data protection, threat modeling, auditability, observability, resiliency, human oversight, and production readiness.
• Engineering and advisory: Python or TypeScript prototypes, architecture decision records, delivery tradeoffs, collaboration with service owners, and cross team facilitation.

Preferred Experience

• AWS AI services, Claude, Kong Konnect AI/MCP integration, Splunk or CloudWatch, CI/CD, and engineering managed services in a regulated enterprise.