Role: Gen AI Solution Architect (Generative AI / Cloud-Native / Enterprise Architecture)
Location: Berlin, CT (100% On-site)
Compensation: $104.00/hr on W2 OR $128/hr on C2C
Duration: 6 Months
Position Overview
Seeking an enterprise-grade Gen AI Solution Architect with 10+ years of experience to lead the end-to-end design, cloud-native architecture, and deployment of enterprise Generative AI and Machine Learning platforms. This 100% on-site role focuses on designing API-led AI architectures, integrating large language models (LLMs) into core enterprise systems, building scalable data pipelines, and establishing reusable architectural patterns across multi-functional engineering PODs.
Key Responsibilities
* End-to-End Gen AI Architecture: Define and architect comprehensive enterprise AI solutions spanning foundation models, RAG (Retrieval-Augmented Generation) frameworks, data pipelines, API gateways, and downstream business application interfaces.
* Cloud-Native & API-Led Design: Architect scalable, resilient, and secure cloud-native AI infrastructures in alignment with enterprise security guidelines and corporate governance.
* Model & Pipeline Integration: Ensure seamless technical integration between AI/ML models, data platforms, feature stores, and consuming enterprise applications.
* Architectural Guardrails & Patterns: Establish reusable architecture blueprints, reference designs, and operational guardrails to standardize AI/ML delivery across PODs.
* Performance, Security & Resilience: Optimize model inference latency, throughput, token usage, data encryption, access controls, and overall system maintainability for production readiness.
* Cross-POD Technical Leadership: Collaborate across engineering PODs, data teams, and executive stakeholders to drive solution alignment and technical consensus.
Required Skillset
* Experience: 10+ years of dedicated professional experience in enterprise software architecture, cloud-native systems, and AI/ML solution engineering.
* Gen AI & LLM Architecture: Direct hands-on architectural experience implementing Generative AI solutions, LLM orchestration frameworks (e.g., LangChain, LlamaIndex), vector databases, and RAG architectures.
* Cloud Platform Mastery: Deep proficiency with cloud-native AI/ML and data ecosystems (AWS, Azure, or Google Cloud Platform) and microservices API patterns.
* Data Engineering & Integration: Expertise in architecting real-time and batch data pipelines, data lakehouse integrations, and RESTful API layers.
* Enterprise Security & Governance: Knowledge of AI security principles, IAM policies, model governance, and data privacy frameworks.
Preferred Qualifications
* Industry certifications in Cloud Architecture (e.g., AWS Certified Solutions Architect - Professional, Azure Solutions Architect) or AI/ML Specializations.
* Experience in utility, energy, or regulated industry domains.
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