Staff Backend AI Engineer, Remote

Overview

We are looking for a Staff Software Engineer to lead the delivery of high-throughput, large-scale transactional systems and agentic AI applications. You will serve as a technical anchor across engineering squads - setting the bar for code quality, cloud architecture, and engineering excellence while mentoring the next generation of engineers. You will report to the Sr. Principal Engineer.

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.

• 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.