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Backend Ai Engineer Jobs (NOW HIRING)

MLabs

Staff Software Engineer - Backend & AI Infra

Staff Software Engineer - Backend & AI Infra Remote Full-time Location: Based in US to GMT timezones Compensation: Competitive Compensation Package Our client is a high-growth technology firm. They ...

Fortinet

Applied AI Engineer - AI Agent

Sunnyvale, CA · On-site

$179K - $220K/yr

Collaboration Work with senior backend engineers to build data pipelines that power AI-driven ... features. Collaborate with design and frontend engineers to translate complex backend/AI systems ...

Fortinet, Inc.

Applied AI Engineer - AI Agent

Sunnyvale, CA · On-site

$179K - $220K/yr

You'll work alongside senior engineers, product managers, and AI researchers to build systems that ... What You'll Do Development • Build and maintain backend services and AI-integrated features for ...

Posh

Senior Software Engineer, Backend (AI)

New York, NY · On-site

$200K - $225K/yr

About the Role We're looking for a Senior Backend Engineer to join our newly formed AI R&D pod-a small, fast-moving team dedicated to building the future of AI-native product experiences at Posh.

Fortinet, Inc.

Staff Engineer - AI Agent

Sunnyvale, CA · On-site

We're looking for an Applied AI Engineer with strong backend and AI experience who can architect, build, and scale secure, performant systems. You'll work closely with product, AI/ML, and design ...

Fortinet

Staff Engineer - AI Agent

Sunnyvale, CA

We're looking for an Applied AI Engineer with strong backend and AI experience who can architect, build, and scale secure, performant systems. You'll work closely with product, AI/ML, and design ...

Fortinet

Staff Engineer - AI Agent

Sunnyvale, CA · On-site

We're looking for an Applied AI Engineer with strong backend and AI experience who can architect, build, and scale secure, performant systems. You'll work closely with product, AI/ML, and design ...

Fortinet, Inc.

Staff Engineer - AI Agent

Sunnyvale, CA · On-site

We're looking for an Applied AI Engineer with strong backend and AI experience who can architect, build, and scale secure, performant systems. You'll work closely with product, AI/ML, and design ...

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All JobsBackend Ai Engineer Jobs

Backend Ai Engineer information

See salary details

$60.5K

$147.7K

$199K

How much do backend ai engineer jobs pay per year?

As of Jun 21, 2026, the average yearly pay for backend ai engineer in the United States is $147,662.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,000.00 and $172,000.00 per year, depending on experience, location, and employer.

What is the difference between Backend Ai Engineer vs Data Scientist?

AspectBackend Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; knowledge of programming, AI frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops AI models, integrates AI into backend systems, collaborates with software teamsAnalyzes data, builds models, interprets data insights, collaborates with business teams
Industry UsageTech companies, AI startups, software firmsResearch institutions, tech companies, finance, healthcare
Common Search/ComparisonYesYes

While both roles involve working with AI and data, Backend Ai Engineers focus on integrating AI models into backend systems and developing scalable AI solutions. Data Scientists primarily analyze data, build predictive models, and generate insights. The roles often overlap in skills and tools but differ in their core focus—system integration versus data analysis.

What are some common challenges Backend AI Engineers face when deploying machine learning models to production?

Backend AI Engineers often encounter challenges such as ensuring model scalability, maintaining low latency, and handling diverse data inputs during deployment. Integrating models into existing backend systems can also require careful consideration of APIs, security, and resource management. Additionally, monitoring model performance and updating models with new data are ongoing responsibilities that require close collaboration with data scientists, DevOps, and product teams.

What is a Backend AI Engineer?

A Backend AI Engineer is a software engineer who specializes in building and maintaining the server-side infrastructure for artificial intelligence applications. Their work involves designing APIs, integrating machine learning models, managing databases, and ensuring efficient data flow between systems. They collaborate with data scientists and frontend developers to deploy AI models at scale and make them accessible through robust backend services. Key skills for this role include programming (often in Python, Java, or similar languages), cloud computing, and knowledge of AI frameworks.

What are the key skills and qualifications needed to thrive as a Backend AI Engineer, and why are they important?

To thrive as a Backend AI Engineer, you need strong programming skills (especially in Python or Java), a deep understanding of algorithms and data structures, and a background in computer science or related fields. Familiarity with AI/ML frameworks (like TensorFlow or PyTorch), RESTful APIs, databases, and cloud platforms is typically expected, along with relevant certifications. Exceptional problem-solving abilities, teamwork, and effective communication are soft skills that distinguish top performers. These competencies are crucial for designing robust, scalable AI solutions that integrate seamlessly with backend systems and drive innovation.
What cities are hiring for Backend Ai Engineer jobs? Cities with the most Backend Ai Engineer job openings:
What states have the most Backend Ai Engineer jobs? States with the most job openings for Backend Ai Engineer jobs include:
Backend Ai Engineer jobs near you

Staff Software Engineer - Backend & AI Infra

MLabs

Remote

Full-time

Posted 6 days ago

Job description

Staff Software Engineer - Backend & AI Infra
Remote Full-time
Location: Based in US to GMT timezones
Compensation: Competitive Compensation Package
Our client is a high-growth technology firm. They are seeking a Staff Software Engineer to spearhead two critical domains: the core agent runtime and backend infrastructure powering a high-frequency trading fleet, and the comprehensive migration of model hosting and agent deployment to in-house, proprietary infrastructure.
This is a foundational, high-impact building role. The successful candidate will design and implement the backend services, runtime engines, and deployment systems that enable a fleet of autonomous agents to operate with superior speed, reliability, and intelligence. By moving away from third-party LLM providers and hosted platforms, this role will establish the sovereign infrastructure necessary for the next generation of autonomous financial software.
Key Responsibilities
Agent Runtime & Backend Development
  • Plugin Runtime Ownership: Lead the evolution of the per-agent process, migrating from a distributed Go/Python hybrid to a centralized, high-performance Go service utilizing Postgres state and real-time websocket price feeds.
  • Rules Engine Engineering: Build a YAML-configurable "Scanner Gateway" to bridge signal production and execution, allowing for complex scoring and filtering without direct code manipulation.
  • Advanced Execution Systems: Develop and maintain the RatchetStop Backend, a centralized profit-trailing service capable of sub-second evaluation and websocket-based order execution to protect capital even when agents are offline.
  • Data & Connectivity: Manage the Model Context Protocol (MCP) server bridging agents to platform tools, and oversee a high-throughput data pipeline (Redis, Postgres, ClickHouse) for real-time market intelligence ingestion.

Model & Agent Hosting Migration
  • Infrastructure Sovereignty: Lead the technical execution of migrating agents from third-party platforms to a custom-built, Senpi-hosted environment featuring isolated workspaces and state persistence.
  • Model Serving: Evaluate and implement the transition from external LLM APIs (Anthropic, Google) to self-hosted inference, optimizing for telemetry capture and performance.
  • Telemetry & Feedback Loops: Architect systems to capture every agent decision and score, creating a self-reinforcing loop where the fleet learns and improves from collective performance data.
  • Deployment Pipelines: Build robust CI/CD pipelines for zero-downtime rollouts, ensuring that updates to scanner logic or runtime patches do not interrupt active market positions.

Infrastructure & Operations
  • System Reliability: Design monitoring and alerting frameworks to detect agent failures, state corruption, or authentication expirations before they impact financial performance.
  • Cloud Orchestration: Manage AWS/EKS environments using Infrastructure-as-Code (IaC).
  • Incident Response: Own the operational health of the fleet, acting as the primary responder for high-stakes trading system incidents.

IInterview Process
  1. Founder / CEO Interview: Introduction to the vision and strategic goals.
  2. Take-Home Test: A practical assessment of technical design and coding capabilities.
  3. Technical Interview: A deep dive into systems architecture and engineering expertise.
  4. Final Interview: Cultural alignment and final technical synthesis.

Requirements
  • Technical Essentials
    • Expert Backend Engineering: Proficiency in writing production-grade code in Go, Python, and Node.js/TypeScript (Go is strongly preferred for runtime services).
    • Startup Experience: A proven track record of building complex backend services (APIs, job scheduling, distributed systems) from scratch in a fast-paced environment.
    • Real-Time Systems: Deep understanding of low-latency environments, websocket management, and sub-second condition evaluation.
    • Database Mastery: Production experience with Postgres, Redis, and at least one analytical database (e.g., ClickHouse, TimescaleDB, or BigQuery).
    • Orchestration: Hands-on experience deploying, scaling, and debugging production workloads on Kubernetes (AWS EKS).
    • End-to-End Ownership: Demonstrated ability to design, build, deploy, and maintain systems throughout their entire lifecycle.

  • Preferred Qualifications
    • LLM Infrastructure: Experience with model serving and optimizing inference (e.g., vLLM, TGI, or TensorRT-LLM).
    • FinTech/Trading: Background in exchange APIs, wallet operations, or on-chain infrastructure where uptime has direct financial consequences.
    • Agentic Frameworks: Familiarity with Model Context Protocol (MCP) or orchestrating multi-agent platforms.

Benefits
    • Competitive compensation and equity packages.
    • The opportunity to build foundational infrastructure in a new category of autonomous software.
    • High-autonomy environment with a focus on engineering excellence.
    • Collaborative culture working alongside industry-leading founders and engineers.

Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.
Commitment to Equality and Accessibility:
At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city.
MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd's Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.

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