Java
Go Programming (Golang)
Python
Redis
Elastic Search
Amazon Web Services (AWS)
grafanaDirector of Engineering — Flights Platform
AI-First Travel Commerce · High-Scale Distributed Systems · Marketplace Infrastructure
🌏 The Problem Space
A flight search looks trivially simple. It is anything but.
Every query you fire triggers a choreography of distributed systems operating in real-time — integrating with a dozen airline GDS/NDC providers, computing dynamic fares across inventory buckets and fare rules, ranking thousands of itineraries by relevance and business intent, and returning a ranked, priced, bookable result set — all in under 100ms.
→ Millions of search queries per minute
→ <100ms end-to-end SLA with external API dependencies
→ High-value transactions — a bug here means a missed booking, not a failed render
→ Pricing errors erode trust faster than any other failure mode
We are rebuilding the Flights platform as a real-time commerce engine for Bharat — AI-native from day zero, built to power both B2C consumer journeys and high-stakes B2B enterprise corridors.
This is a once-in-a-decade opportunity to build national-scale flight infrastructure from first principles.
🧠 What You Will Own
You will own the full Flights platform — systems, architecture, and the teams that build them.
Core System Domains:
•Search Systems — high-throughput, low-latency query pipelines returning ranked, bookable options
•Pricing & Fare Engine — dynamic pricing logic, fare rules, promotional overlays, and real-time validation
•Booking & Ticketing — transaction-critical flows requiring strict consistency, idempotency, and zero data loss
•Airline Integrations — managing unreliable external GDS/NDC APIs with retries, circuit-breakers, and reconciliation
•Post-Booking Flows — cancellations, modifications, refunds — correctness at the margin is non-negotiable
Platform Scope:
•High-scale APIs serving consumer apps, B2B enterprise clients, and third-party partners
•Event-driven state machines managing booking workflows across async boundaries
•Observability and reliability infrastructure across all mission-critical flows
Team Scope:
•Lead 15–30+ engineers across multiple product and platform teams
•Manage Engineering Managers and Principal/Staff engineers
•Own hiring, org design, and technical direction
⚙️ Core Engineering Challenges
This role is fundamentally about making the right trade-offs under uncertainty — at scale.
Latency vs. Accuracy — when do you serve a cached fare vs. call a live airline API?
Availability vs. Consistency — graceful degradation at booking time vs. strict price validation
Cost vs. Performance — when is an external API call worth it vs. a cache hit?
Scalability vs. Simplicity — the best system is the one your team can reason about under incident
🤖 AI-First Engineering
AI is not an afterthought. It is load-bearing architecture.
•LLM-powered pricing intelligence — dynamic fare prediction and demand signals
•RAG pipelines for fare rules, refund policy, and support automation
•Agentic booking resolution workflows — autonomous exception handling at scale
•MCP-based orchestration layers for multi-provider integration
⚖️ Key Responsibilities
Architecture & Distributed Systems
•Design and evolve sub-100ms distributed query systems serving millions of concurrent searches
•Build fault-tolerant booking pipelines with strong consistency and durability guarantees
•Drive Kafka-based event architectures for booking state management
Reliability & Observability
•Own 99.99%+ availability for booking and pricing systems
•Build deep observability — metrics, distributed tracing, structured logging, SLOs/SLAs
•Lead post-incident reviews and drive systemic reliability improvements
Business Partnership
•Partner with Product, Revenue, and Partnerships to translate commercial goals into architecture
•Influence platform roadmap, supplier strategy, and long-term technical investment
🛠️ Technology Stack
Backend: Java · Kotlin · Go · Python
Architecture: Microservices · Event-Driven (Kafka) · gRPC
Data: Redis · Aerospike · DynamoDB · Elasticsearch
Cloud: AWS (EKS, EC2, S3)
Observability: Prometheus · Grafana · OpenTelemetry
👤 Who You Are
•12–16 years in backend/distributed systems; 5+ Years in an Engineering Leadership role, led teams of 15–50 engineers
•Built and scaled large B2C + B2B platforms — Travel Tech, FinTech, or high-scale Consumer
•Deep expertise in real-time systems, marketplace dynamics, and external API integration
•Tier-I institute background strongly preferred (IIT / IIIT / NIT / IISC / BITS / VIT / SRM — CSE/ISE)
🚀 Why This Matters
Build national-scale infrastructure for 1.4 billion people
Sit at the intersection of AI · distributed systems · marketplace economics
Define the future of travel commerce in India — from architecture to product
Shubham Vishwakarma
Full Stack Developer - Averlon
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