Principal Solution Architect (Multi-Cloud, Data & Agentic AI)
Obin AI
- Location
- Onsite (NYC-Metro, New York)
- Employment
- Full-time
- Level
- Senior Level
Posted 1 week ago
About the Role
Obin AI is building the future of financial services using deep domain AI agents. This role will design architectural strategies for enterprise multi-cloud platforms and next-generation AI initiatives at leading financial institutions.
Skills
Multi-Cloud Architecture
Agentic AI
Generative AI
Kubernetes
Terraform
Apache Spark
RAG
Vector Databases
GCP
AWS
Azure
Distributed Systems
Data Pipelines
Microservices
Prompt Routing
Infrastructure as Code
Full job details
The Role
We are seeking an industry-leading Principal Solution Architect to design the architectural strategy for enterprise multi-cloud platforms and next-generation AI initiatives at financial firms.
In this elite role, you will bring Obin’s agentic capabilities and land them within the complex technical environments of leading financial institutions. You will design distributed multi-cloud architectures (GCP, AWS, Azure) capable of running high-throughput data pipelines, optimizing latency of LLM calls, and orchestrating state-of-the-art Agentic AI workflows (collaborative multi-agent protocols, generative storytelling, and autonomous task delegation). You are a technical visionary who translates non-deterministic agentic capabilities and complex distributed computing into robust production software.
Key Responsibilities
- Agentic AI & Collaborative Frameworks: Design and build autonomous, multi-agent ecosystems. Implement cutting-edge agent-to-agent (A2A) orchestration protocols, enabling secure task delegation, runtime state handoffs, and collaborative workflows without context pollution.
- Generative AI: Architect infrastructure to support sophisticated Generative AI applications, including Retrieval-Augmented Generation (RAG), voice agents, streaming agent output, and vector database routing.
- Multi-Cloud Infrastructure & Kubernetes Mastery: Build, secure, and scale containerized applications and microservices topologies natively across Google Cloud, AWS, and Azure. Establish highly declarative environments using Infrastructure as Code (Terraform) and advanced Kubernetes orchestration (GKE, EKS).
- Distributed Enterprise Data Pipelines: Architect decoupled data ecosystem frameworks to ingest and shard massive streams of structured and unstructured data. Run distributed processing engines like Apache Spark on Kubernetes alongside cloud-native data warehouses (BigQuery, Snowflake).
- Technical Advocacy & Inner-Sourcing: Champion technical excellence by publishing reusable blueprints, reference code architectures, and technical documentation. Act as a cross-functional leader aligning research teams, core engineering, and executive stakeholders.
Required Skills & Experience
1. Agentic AI & Generative Engineering
- Advanced AI Paradigms: Proven experience architecting multi-agent orchestration frameworks, prompt-routing middleware, and self-correcting agent loops.
- AI architectures: Experience with implementing RAG systems, agent harnesses, deep research agents and other agentic workflows
2. Multi-Cloud & Enterprise Data Foundations
- Distributed Systems: Expert-level knowledge running heavy analytical workloads (e.g., Spark, Airflow) natively inside containerized ecosystems (Kubernetes).
- Cloud Topologies: Comprehensive, production-level engineering experience across at least two hyperscalers (GCP or AWS or Azure).
- Data Mechanics: Strong grasp of modern data storage paradigms, including columnar storage, vector indexing, and automated data lake governance.
3. Leadership & Vision
- Experience acting as a CTO, Principal Architect, or Strategic Lead driving large-scale digital transformations or public-sector AI cloud implementations.
- Strong background in developer advocacy, open-source contributions, or technical publication.