---
title: 'AI Engineer, AIOps & Infrastructure at Eloquent AI'
canonical: 'https://feeny.ai/job/ai-engineer-aiops-infrastructure-eloquent-ai-san-francisco-1me2s9503a7q'
type: 'job'
last_seen: '2026-09-06'
---

# AI Engineer, AIOps & Infrastructure at Eloquent AI

- **Company:** Eloquent AI
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-08-22
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/eloquentai/550ca2ac-4420-48fb-a37f-e765053d7e7f

## Job description

## MEET ELOQUENT AI

At Eloquent AI, we’re building the next generation of AI Operators—multimodal, autonomous systems that execute complex workflows across fragmented tools with human-level precision. Our technology goes far beyond chat: it sees, reads, clicks, types, and makes decisions—transforming how work gets done in regulated, high-stakes environments.

We’re already powering some of the world’s leading financial institutions and insurers, fundamentally changing how millions of people manage their finances every day. From automating compliance reviews to handling customer operations, our Operators are quietly replacing repetitive, manual tasks with intelligent, end-to-end execution.

Headquartered in San Francisco with a global footprint, Eloquent AI is a fast-growing company backed by top-tier investors. Join us to work alongside world-class talent in AI, engineering, and product as we redefine the future of financial services.

## Your Role

As a Senior Software Engineer, AIOps & Infrastructure at Eloquent AI, you will be responsible for designing, building, and optimizing scalable, high-performance AI infrastructure to support the deployment and operation of our enterprise AI agents. Your work will enable machine learning engineers and AI teams to train, fine-tune, and deploy LLMs efficiently while ensuring stability, observability, and performance at scale.

You’ll play a key role in automating LLMOps and MLOps workflows, optimizing GPU workloads, and ensuring resilient, production-ready AI systems. This role requires deep expertise in cloud infrastructure, Kubernetes, and LLM and ML deployment pipelines. If you’re passionate about scalable AI systems and optimizing ML models for real-world applications, this is your opportunity to work at the frontier of LLMOps.

You will:

- Design and build scalable ML infrastructure for deploying and maintaining AI agents in production.
- Automate LLMOps and MLOps workflows, ensuring seamless model training, fine-tuning, deployment, and monitoring.
- Optimize GPU and cloud compute workloads, improving efficiency and reducing latency for large-scale AI systems.
- Develop Kubernetes-based solutions, including custom operators for ML model orchestration.
- Improve system observability and reliability, implementing logging, monitoring, and performance tracking for AI models.
- Work with ML and engineering teams to streamline data pipelines, model serving, and inference optimizations.
- Ensure security, compliance, and reliability in AI infrastructure, maintaining high availability and scalability.
- Participate in on-call rotations, ensuring 24/7 reliability of critical AI systems.

## REQUIREMENTS

- 5+ years of experience in software engineering, MLOps, or infrastructure development.
- Strong expertise in Kubernetes and experience managing containerized ML workloads.
- Deep understanding of cloud platforms (AWS, GCP, Azure) and distributed computing.
- Proficiency in Python, with experience developing services for ML/AI applications.
- Experience with ML model deployment pipelines, including model serving, inference optimization, and monitoring.
- Familiarity with vector databases, retrieval systems, and RAG architectures is a plus.
- Strong problem-solving skills and the ability to work in a high-scale, production-focused AI environment.

Bonus Points If…

- You have experience with LLMOps, fine-tuning, and deploying large-scale AI models.
- You’ve worked with GPU workload optimization, ML model parallelization, or distributed training strategies.
- You have experience building infrastructure for AI-powered applications.
- You’ve contributed to open-source MLOps tools or AI infrastructure projects.
- You thrive in a fast-moving startup environment and enjoy solving complex technical challenges.

## About Eloquent AI

## Company Overview
- **One-liner**: Eloquent AI builds autonomous AI Operators for financial services that automate complex, regulated customer operations by observing existing workflows without requiring APIs or engineering effort.
- **Entity Type**: Private (Seed stage, raised $10M seed round)
- **Headquarters**: San Francisco, California, USA (with an office in London, UK)
- **Founded**: 2025
- **Founders**: Tugce Bulut and Dr. Aldo Lipani

## Core Business
- **Primary industry/industries**: Artificial Intelligence, Financial Services (Banking, Fintech, Insurance)
- **Target customers**: B2B, specifically regulated financial institutions including banks, fintechs, and insurance companies (Enterprise segment)
- **Mission or purpose statement**: To build the operating system for companies running in the age of AI, freeing people from repetitive work so they can spend their time on something better. The company’s tagline: *"Work should not feel like a loop."* [eloquentai.co](https://www.eloquentai.co/)

## Products & Services
- **AI Operator for Financial Services**: An autonomous AI agent that learns to navigate existing systems by observing standard operating procedures (SOPs) and human actions. It can automate up to 96% of complex, regulated customer service tasks (e.g., account unfreezing, AML/KYC checks, loan repayment adjustments, policy re-issuance, debt recovery, cash advance management) without any APIs or engineering integration. It is deployable in weeks, supports chat, voice, and email, and includes built-in compliance guardrails, an audit trail, and a proprietary LLM (Oratio) trained on financial regulations. [eloquentai.co](https://www.eloquentai.co/) [ycombinator.com](https://www.ycombinator.com/companies/eloquent-ai)
- **Evals Framework & Oratio Fin Model**: A proprietary evaluation and compliance system that uses simulators and counterfactual evaluators to rigorously test and approve modifications before deployment. The Oratio Fin model is a specialized LLM trained specifically on financial regulations to ensure auditable, compliant decision-making. [eloquentai.co](https://www.eloquentai.co/)

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: $500K ARR achieved in just four weeks from launch; 11x ARR growth in the first year. [ycombinator.com](https://www.ycombinator.com/companies/eloquent-ai) [eloquentai.co](https://www.eloquentai.co/careers)
- **Total Funding**: $10 million seed round raised shortly after launch. [eloquentai.co](https://www.eloquentai.co/careers)
- **Notable Investors/Partners**: Y Combinator (Spring 2025 batch). Lead investors not named on the careers page, but the company is YC-backed. [ycombinator.com](https://www.ycombinator.com/companies/eloquent-ai)
- **Growth Signals**: Onboarded major banks and fintechs in under a year; demand is described as "accelerating fast." The company is actively hiring across 12 open positions in San Francisco and London. [eloquentai.co](https://www.eloquentai.co/careers)

## Competitive Advantages
- **No-Integration Deployment**: Unlike generic AI agents that require cumbersome API integrations and long development cycles, Eloquent AI learns by simply observing existing workflows (SOPs) and team actions. This allows deployment in weeks, not months, with no engineering effort required from the customer.
- **Purpose-Built for Regulated Industries**: The company is exclusively focused on financial services, with a proprietary LLM (Oratio) trained on financial regulations. This gives it a deep, defensible moat in a high-stakes, high-compliance market where generic AI models cannot operate safely.
- **Data Privacy & Security**: The platform offers private deployment in a customer’s VPC or on-premises, and explicitly states that customer data is never used to train its models. PII is encrypted in transit and at rest, with customizable redaction. [eloquentai.co](https://www.eloquentai.co/)
- **Proven Traction**: Hitting $500K ARR in four weeks and growing 11x year-over-year with major financial institutions as customers demonstrates strong product-market fit and rapid enterprise adoption.

## Strategic Focus
- **Scale the Team**: The company is in a hypergrowth phase, actively building out its engineering, product, and deployment teams across San Francisco and London to match accelerating demand.
- **Deepen Financial Services Vertical**: Continued focus on automating increasingly complex, multi-party workflows within banking, fintech, and insurance, with a strong emphasis on compliance and auditability.
- **Product Expansion**: Likely expanding the capabilities of its AI Operator to cover more use cases and integrate more deeply with existing enterprise systems, all while maintaining its no-engineering, observation-based approach.

## Why Work Here
- **High Impact**: The systems built directly automate critical, regulated operations for major financial institutions, freeing people from repetitive work. [eloquentai.co](https://www.eloquentai.co/careers)
- **Full Ownership & Autonomy**: Small team with high autonomy; engineers own what they ship end-to-end. [eloquentai.co](https://www.eloquentai.co/careers)
- **Hypergrowth Environment**: 11x ARR growth in a year, $10M seed funding, and accelerating demand. The company is at a very early stage (team size of ~5 as of YC batch), offering significant upside and influence. [eloquentai.co](https://www.eloquentai.co/careers) [ycombinator.com](https://www.ycombinator.com/companies/eloquent-ai)
- **Top-Tier Compensation**: Competitive salary and meaningful equity; the careers page specifically mentions "company offsite in Italy." [eloquentai.co](https://www.eloquentai.co/careers)
- **Work Policy**: Hybrid/On-site in San Francisco (on-site for most roles) and Remote for some roles in London. Specific roles list "On-site" (SF) or "Remote" (London). [eloquentai.co](https://www.eloquentai.co/careers) [ycombinator.com](https://www.ycombinator.com/companies/eloquent-ai/jobs)
- **Founding Team**: Led by a second-time entrepreneur (Tugce Bulut, who previously scaled Streetbees to 200 people and $80M in funding) and a Machine Learning professor (Dr. Aldo Lipani from UCL). [ycombinator.com](https://www.ycombinator.com/companies/eloquent-ai)

## Sources
1. [eloquentai.co](https://www.eloquentai.co/)
2. [eloquentai.co/careers](https://www.eloquentai.co/careers)
3. [ycombinator.com](https://www.ycombinator.com/companies/eloquent-ai)
4. [ycombinator.com](https://www.ycombinator.com/companies/eloquent-ai/jobs)
5. [linkedin.com](https://www.linkedin.com/company/eloquentai)

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