Senior Backend Engineer- AI Agents (Remote)

Ovii's Interpretation of the Role

Senior Backend Engineer driving the design and implementation of high‑scale, real‑time backend services that power AI agents. Work across distributed systems, cloud infrastructure, and LLM‑enabled applications to deliver production‑grade AI experiences.

Role Snapshot

• Build scalable backend for AI agents
• Design low‑latency inference pipelines
• Develop orchestration and event‑driven frameworks
• Maintain robust REST & gRPC APIs
• Collaborate with ML, product, and solutions teams
• Drive observability, safety, and performance

Must-Have Requirements

• backend engineering
• distributed systems
• high‑scale production systems
• real‑time/event‑driven architecture
• API design (REST, gRPC)
• SQL & NoSQL databases
• Docker & Kubernetes
• cloud platforms (AWS, GCP, Azure)
• platform engineering

Nice-to-Have Signals

• LLM integration / conversational AI
• agent frameworks / multi‑step reasoning
• RAG pipelines & vector databases
• evaluation frameworks for AI agents
• prompting strategies & context windows
• exposure to real‑time decisioning systems
• familiarity with workflow orchestration engines
• LLM / conversational AI
• AI agent production

Work Setup

• Location: United States, United States
• Work mode: REMOTE
• Remote scope: UNSPECIFIED
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: unknown

Not Specified in JD

• Salary range
• Visa sponsorship
• Security clearance
• Coding test

What You'll Likely Work On

• Design and implement high‑throughput, low‑latency backend services for AI agents
• Create agent orchestration frameworks supporting multi‑step reasoning and tool usage
• Build memory, context‑management, and state‑persistence layers for agents
• Architect inference pipelines that combine LLMs, custom models, and external services
• Develop evaluation frameworks to measure agent accuracy, reliability, and safety
• Enable continuous improvement loops from feedback to retraining and deployment
• Partner with Applied AI/ML teams to productionize models and agent behaviours
• Establish best practices for observability, monitoring, and guardrails

Good Fit If You Have

• Experience with LLMs or conversational AI products
• Familiarity with retrieval‑augmented generation or vector databases
• Exposure to AI evaluation methods (offline/online evals, A/B testing)