Full-Time
Staff Backend AI Engineer
Posted on 8/18/2026
Experian
1-10 employees
Venture capital arm funding data startups
Compensation Overview
$115.7k - $208.3k/yr
United States
Remote
Bachelor's, Master's
 Software Engineering (2) |
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- A B.S. or M.S. degree in Computer Science, Software Engineering, or a related technical discipline is required.
- At least 8 years of professional software engineering experience, including at least 3 years in a staff-level, principal, or equivalent technical leadership role, is required.
- At least 4 years of hands-on experience building and operating production services on Amazon Web Services, including ECS/Fargate, EKS, Lambda, S3, RDS, DynamoDB, SQS, Kafka, VPC, API Gateway, and CloudFront, is required.
- At least 2 years of professional Python development experience with asyncio, FastAPI, and Pydantic, and at least 2 years of production Go experience, is required.
- Experience architecting and operating large-scale transactional systems, including high-volume OLTP, event-driven architectures, distributed caches, and saga/outbox patterns, is required.
- Hands-on experience building agentic AI systems, including agent orchestration, tool or function calling, retrieval-augmented generation pipelines, and large language model integration patterns, is required.
- Command of relational and non-relational databases such as PostgreSQL, Aurora, DynamoDB, Redis, or Elasticsearch, including query optimization and schema design at scale, is required.
- Proficiency with containerization and infrastructure as code using Docker, Terraform, CDK, or Helm is required.
- Experience with observability tooling such as Datadog, OpenTelemetry, CloudWatch, or equivalent tools is required.
- Experience owning and evolving continuous integration and continuous delivery pipelines using Jenkins, GitHub Actions, or Harness is required.
- Experience integrating asynchronous messaging systems such as Kafka and SQS and designing event-driven architectures is required.
- Experience mentoring engineers and driving company-level improvements in engineering culture, quality, and velocity is required.
- Architect, build, and own services for large-scale transactional platforms, ensuring high availability, fault tolerance, and sub-second performance at millions of transactions per second.
- Lead the end-to-end design of agentic AI workflows using orchestration frameworks such as LangGraph, AutoGen, and CrewAI, implementing tool-calling patterns and multi-agent coordination on Amazon Web Services.
- Write production-grade Python and Go services and establish language-specific idioms, patterns, and performance baselines adopted across engineering teams.
- Design and govern Amazon Web Services-native infrastructure using ECS, EKS, Lambda, MSK, RDS Aurora, DynamoDB, SageMaker, or EventBridge in alignment with the AWS Well-Architected Framework.
- Establish engineering standards for code reviews, test coverage, continuous integration and continuous delivery pipelines, and observability instrumentation including distributed tracing, structured logging, and alerting.
- Conduct and lead technical design reviews for new services, integrations, and platform changes, and produce architecture decision records and technical specifications.
- Resolve performance bottlenecks in distributed systems through database query optimization, caching strategies, and asynchronous processing patterns.
- Guide proof-of-concept work for new technologies, evaluate production readiness, and present recommendations to engineering leadership.
- Mentor and develop senior and mid-level engineers through structured code reviews, pairing sessions, and technical coaching.
- Contribute to on-call rotations, incident response, and post-mortem processes to guide systemic reliability improvements.
Experian Ventures is the venture capital arm of Experian, a global information services company. It provides investment capital and strategic partnerships to startups, helping them grow by leveraging Experian’s data assets, technology, and global network. The fund focuses on backing entrepreneurs who can disrupt data- and tech-driven markets, using Experian’s platforms and reach to accelerate portfolio companies. Unlike standalone funds, it differentiates itself with access to Experian’s scale, data resources, and worldwide offices, enabling closer collaboration and faster go-to-market support. The goal is to fund and mentor startups that can shape the future of information services while expanding Experian’s ecosystem and influence across regions.
Company Size
1-10
Company Stage
N/A
Total Funding
$82M
Headquarters
Costa Mesa, California
Founded
1995
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Simplify's Take
What believers are saying
- FY26 organic revenue grew 8%, and benchmark operating profit rose 15%.
- Experian launched Snapchat AI Sponsored Snaps on April 28, 2026.
- VantageScore 4.0 through Experian Connect expands rental screening with Zillow adoption.
What critics are saying
- CFPB’s January 7, 2025 lawsuit over dispute handling continues through 2026.
- Generative AI helps banks build internal risk tools, threatening bureau disintermediation.
- Revenue still depends on lending cycles; cautious banks slowed credit-card issuance in FY26.
What makes Experian unique
- Experian’s global bureau scale spans North America, Brazil, and the UK.
- Ascend combines proprietary credit data, identity, fraud, and financial-crime workflows.
- KYC360 acquisition, closed July 17, 2026, deepens compliance and onboarding capabilities.
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Benefits
Remote Work Options
Professional Development Budget
Company News
Experian reported a 26% increase in statutory pre-tax profit to $1.95 billion and announced a $1 billion share buyback programme, yet its stock plunged 7% as investors focused on conservative growth forecasts and AI concerns. The data analytics company posted full-year revenue of $8.45 billion with 15% growth in benchmark operating profit. However, its fiscal 2027 organic revenue growth guidance of 6-8% fell below the 8% analyst consensus. CEO Brian Cassin cited economic volatility and cautious banking clients slowing credit card issuance. The sell-off reflects investor anxiety that generative AI could make traditional credit checking obsolete. Markets interpreted the massive buyback as defensive rather than transformational, questioning whether Experian can compete as banks develop internal AI tools for risk analysis.
Experian has launched an AI chatbot on Snapchat to provide financial advice, targeting younger consumers on a platform they already use. The credit bureau aims to deliver trusted financial information to help build financial literacy amongst users who might not otherwise seek professional guidance. Rob Burnette, CEO of Outlook Financial Center, views AI chatbots as useful tools for answering broad financial questions, such as improving credit scores. However, he cautions that AI cannot address individual circumstances without specific personal data, which users should avoid sharing online. Burnette recommends verifying information sources when using AI chatbots and consulting human advisers for personalised financial decisions. Whilst not threatened by AI, he emphasises its limitations in handling the nuanced, context-specific nature of personal finance.
Xactus has integrated the Experian Verify Preview Report into its Xactus360 Intelligent Verification Platform, providing lenders with upfront visibility into borrower employment data at no additional cost. The tool allows lenders to see which employment records are available for instant verification before ordering a full verification of employment and income report. Previously, lenders had to order a full VOE/I report to determine if usable data existed. Xactus is the first to embed this capability directly within the credit report workflow, eliminating the need for separate verification relationships or additional steps. The enhancement is automatically included for Xactus clients who order credit reports through the platform and use Experian Verify, requiring no new integrations or workflow changes.
Palenca, a Mexican income verification platform for financial institutions, has raised $4 million in a Series A round led by Experian, with participation from Foundation Capital, Gilgamesh Ventures and Dhow Ventures. The company addresses a critical gap in Mexico's financial inclusion: the lack of reliable income data prevents credit expansion to new segments. Without verifiable income information, financial institutions must either limit their reach or assume greater risk. Palenca's platform validates income from various sources, including informal employment, to integrate them into credit and risk decisions. The funding will develop new data products, expand income source validation and strengthen predictive models using artificial intelligence. The company processed nearly 5 million verifications in 2025 and projects reaching 20 million this year, enabling banks to extend credit to previously excluded populations.
Experian has integrated its AI-powered financial education tools into Snapchat's new AI Sponsored Snaps advertising format, allowing users to ask money questions directly within the app's chat experience. The integration aims to transform everyday messaging into an interactive learning and brand engagement channel for younger users. Snap's investment case hinges on whether its combination of augmented reality, AI and Gen Z engagement can generate profitable revenue. The company reported over 110 million US monthly users and 950 billion chats in Q1 2026. The Experian partnership demonstrates how Snap is testing conversational AI to deepen engagement and improve advertising performance. Snap's narrative projects $7.9 billion revenue and $709.3 million earnings by 2029, requiring 10.2% yearly revenue growth. Some analysts forecast $8.5 billion revenue by 2029, though this depends on AR and AI investments delivering stronger returns than currently expected.