SDE IV – Backend Engineer

About the Role

We're looking for a seasoned backend engineer who can architect, build, and scale mission-critical systems powering Portkey's AI infrastructure platform. You should be comfortable owning complex distributed systems end-to-end, driving technical strategy, and raising the engineering bar while working in a fast-paced, product-focused environment.

What You'll Do

• Design and build highly scalable, low-latency backend services and APIs powering core Portkey products.
• Lead architecture for major product areas — solving hard distributed systems problems around routing, reliability, observability, performance, and data scale.
• Own system design, implementation, testing, and deployment with strong attention to reliability and correctness.
• Work closely with product, infra, and AI platform teams to deliver features with high velocity and high quality.
• Mentor engineers, influence best practices, and shape long-term technical vision.
• Drive performance optimization, cost efficiency, and operational excellence across backend systems.

What We're Looking For

• 7–10+ years of backend engineering experience with deep expertise in building large-scale distributed systems.
• Strong proficiency in Go, Node.js, Python, or similar languages, along with experience in microservices architectures.
• Expertise in both SQL and NoSQL systems (e.g., Postgres, MySQL, Redis, DynamoDB, Cassandra, etc.).
• Strong grasp of caching, queues, and event-driven architectures.
• Solid understanding of AWS/GCP, container orchestration, and modern infra/tooling.
• Experience designing and operating high-throughput, high-availability systems.
• High ownership, excellent judgment, and ability to thrive in a fast-paced environment.
• Startup or product-centric environment experience is a strong plus.

Bonus

• Experience building analytics systems at scale using ClickHouse or similar OLAP/columnar databases (Pinot, Druid, BigQuery).
• Experience building GenAI applications such as:
• Retrieval-Augmented Generation (RAG) pipelines
• AI Agents / Agentic frameworks
• Vector search systems
• Evaluation pipelines, guardrails, or LLM orchestration
• Experience with AI infrastructure, API gateways, networking layers, or observability platforms.