$240,000–$290,000
Principal Solution Architect (Multi-Cloud, Data & Agentic AI)
Updated
$220,000–$300,000New York, NYPrincipal
Design autonomous multi-agent ecosystems and secure A2A orchestration workflows.
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At a glance
Posted base pay
$220K–$300KAbove the median
Median $225K
This job$220K–$300KTypical staff+ FDE payMiddle 50% of 436 postings$195K–$262KThe work
Builds what the customer runs
Balance
- Mostly building
- Mixed
- Mostly pre-sales or support
Project stages
- Pre-sales (not covered)
- Proof of concept (not covered)
- Implementation
- Operations (not covered)
- Coding
- Writes production code
- Builds for
- External customers
- Level
- Staff+
- Role
- Technical lead
What they ask for
Tools
Less common in FDE jobs
- Company size: About 1–50 people9%
- Company stage: Early12%
- Responsibility level: Staff+17%
- Individual contributor or manager: Technical lead47%
Share of US FDE postings that state each fact.
The job description from Obin AI
Posted by Obin AI on
Build the AI workforce that finance can actually trust.
We are closing the gap between what AI promises and what regulated institutions can responsibly deploy.
If you fall in love with hard problems — not easy answers — this is where your work matters.
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.
Base compensation range
$220,000 - $300,000
Plus Annual Bonus + Equity
About Us
Obin AI is an enterprise artificial intelligence company building the next generation of agentic intelligence for financial services. The company develops a production-ready AI workforce that runs defined workflows end-to-end inside a firm’s controls and audit boundaries, encoding institution-specific logic and producing traceable, inspectable outputs. Because of its open, no-lock-in architecture and ability to resolve even nuanced edge cases, Obin AI is trusted by leading global financial institutions representing over $1 trillion in assets under management. Obin AI enables these organizations to standardize and accelerate their core workflows — continuous monitoring, scalable underwriting, and earlier risk detection — without scaling teams or compromising governance. Founded by seasoned leaders from Google AI, JPMorgan and Silver Lake, Obin AI is reimagining how financial firms operate — deploying AI workers directly within live workflows to expand decision capacity under institutional controls.
Obin AI is an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
About Obin AI
Obin builds production-grade, governed AI agents (Robins) and an end-to-end platform for regulated financial institutions to automate complex workflows inside their own cloud and control boundaries.
Seed · 10–50 people
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