AI Backend Engineer (SDE-2)

Join our rapidly growing AI startup as an AI Backend Engineer and build the agentic core of our platform: the LLM workflows, agent orchestration, and AI-driven systems that turn natural-language marketer intent into live, personalized in-app experiences at scale. This role is for an engineer who pairs strong backend fundamentals with hands-on applied AI, and who wants to own systems end to end on a high-throughput production hot path.

Plotline is backed by Elevation Capital and supports customers like Dream11, Upstox, and Zepto.

WHY THIS ROLE MATTERS

• Build the AI layer that turns marketer intent into live in-app experiences for 300M+ end users.
• Work directly with the engineering team and founders to shape the agentic core of the product.
• Design backend systems and patterns that scale with our high-growth trajectory.
• We're seeking a rare combination of backend rigor, applied AI judgment, hands-on execution, and the drive to own systems end to end.

ABOUT THIS ROLE

Key challenges you'll solve

• Agent Orchestration: Building LLM agents that plan multi-step and use tools reliably, deciding which steps to take rather than following a hardcoded script.
• Production Reliability: Keeping a non-deterministic AI system fast, safe to retry, and observable on a sub-100ms hot path serving millions of devices.
• This is an opportunity to have outsized impact on the core of the product while building deep expertise in agentic systems at a scaling startup.

OUTCOMES EXPECTED

• Own and scale both our core backend and the agentic core, with the data modeling, resilience, and cost controls needed to run them reliably in production at scale.
• Ship grounded, tool-calling agent flows end to end, backed by retrieval and a real evaluation harness.

RESPONSIBILITIES

Agent & AI Systems

• LLM Orchestration: Design agents with tool-calling and real multi-step planning that select tools and recover when a tool fails or returns nothing useful.
• Retrieval (RAG): Build chunking, embedding, and retrieval pipelines that ground the agent's outputs in real data and best practices.
• Evaluation & Guardrails: Build the evals and safeguards needed to measure and trust output quality in a non-deterministic system.

Backend & Infrastructure

• Production Services: Own backend services on a high-throughput, low-latency hot path, with idempotency, resilience, and clean failure handling.
• Data Modeling: Model and query behavioral and profile data to power segmentation, personalization, and campaign logic.
• Latency & Cost: Keep the system fast and economical, avoiding unnecessary model calls and managing budgets as it scales.

REQUIREMENTS

Professional Experience

• 2 to 4 years of overall engineering experience, including 1+ years building AI/LLM systems, with a track record of shipping production systems under real load.
• Hands-on experience building with LLMs (tool-calling, agent orchestration, retrieval, or prompt and context design).
• Comfort with the operational side: timeouts, retries, fallbacks, tracing, and debugging a bad run.

Technical Proficiency

• Backend Languages: Proficiency in one or more of Go, Python, or TypeScript/Node. We care more about how you reason than which stack you have used.
• AI Tooling: Familiarity with LLM APIs, vector search, embeddings, and chunking strategies.
• Systems Fundamentals: Strong data modeling, concurrency, and API design, with a sharp instinct for safe retries and observability.

CORE COMPETENCIES

Engineering Judgment

• Systems Thinking: Designs for scale, reliability, and clear failure modes from the start.
• Quality Standards: Values clear judgment and craft over feature count, and can explain and defend tradeoffs.

Technical Execution

• Self-Sufficiency: Ships complete systems end to end, from data model to deployed service.
• Applied AI Sense: Knows when to use an LLM, when not to, and how to keep outputs grounded and trustworthy.

Startup Agility

• Rapid Iteration: Balances rigor with speed of execution and learning.
• Growth Mindset: Continuously evolves the system and approach based on production signals and feedback.
• Ready to build the AI core of a fast-growing platform? If you're excited by the intersection of solid backend engineering and applied AI, we'd love to hear from you.