Note: The job is a remote job and is open to candidates in USA. Experian is a global data and technology company that powers opportunities for people and businesses through data and advanced technologies. The Staff Backend AI Engineer will lead the delivery of high-throughput transactional systems and agentic AI applications, while setting engineering standards, governing AWS architecture, resolving distributed-system performance issues, and mentoring engineers.
Responsibilities
- 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. Implement these workflows using tool-calling patterns and multi-agent coordination on AWS
- Write production-grade Python and Go services; establish language-specific idioms, patterns, and performance baselines adopted across engineering teams
- Design and govern AWS-native infrastructure (ECS, EKS, Lambda, MSK, RDS Aurora, DynamoDB, SageMaker, or EventBridge) - ensuring solutions align with the AWS Well-Architected Framework
- Establish engineering standards: code review practices, test coverage requirements, CI/CD pipelines, and observability instrumentation (distributed tracing, structured logging, alerting)
- Conduct and lead technical design reviews for new services, integrations, and platform changes; produce high-quality architecture decision records (ADRs) and technical specs
- Resolve performance bottlenecks in distributed systems, including database query optimization, caching strategies, and async processing patterns
- Guide proof-of-concept (PoC) work for new technologies and evaluate their production readiness; present recommendations to engineering leadership
- Mentor and level up 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
Skills
- B.S. or M.S. degree in Computer Science, Software Engineering, or a related technical discipline
- 8+ years of professional software engineering experience, including 3+ years in a staff-level, principal, or equivalent technical leadership role
- 4+ years of hands-on experience building and operating production services on AWS — with deep familiarity across compute (ECS/Fargate, EKS, Lambda), storage (S3, RDS, DynamoDB), messaging (SQS, Kafka), and networking (VPC, API Gateway, CloudFront)
- 2+ years of professional Python development with command of async patterns (asyncio, FastAPI, Pydantic); 2+ years of Go in production microservices
- Demonstrated experience architecting and operating large-scale transactional systems (high-volume OLTP, event-driven architectures, distributed caches, saga/outbox patterns)
- Hands-on experience building agentic AI systems — including agent orchestration, tool/function calling, RAG pipelines, and LLM integration patterns
- Command of relational and non-relational databases (PostgreSQL, Aurora, DynamoDB, Redis, or ElasticSearch) with experience with query optimization and schema design at scale
- Proficiency with containerization and infrastructure-as-code (Docker, Terraform, CDK, or Helm)
- Experience with observability tooling: Datadog, OpenTelemetry, CloudWatch, or equivalents
- Experience owning and evolving CI/CD pipelines using tools like Jenkins, GitHub Actions or Harness
- Experience integrating async messaging systems (Kafka, SQS) and designing event-driven architectures
- Experience mentoring engineers and driving company level improvements in engineering culture, quality, and velocity
Benefits
- Bonus plan
- Medical, dental, and vision benefits
- Matching 401K
- Flexible work environment, ability to work remote, hybrid or in-office
- Volunteer time off
- Vacation
- Sick leave
- 12 paid holidays
- Variable pay opportunity
Company Overview
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