Website:
grull.space
Job details:
JOB DESCRIPTION
Software Engineer — Digital Asset Intelligence & Trading Systems
grull.space | Bangalore, India | Full-Time, On-Site
Location
Bangalore, India
Work Mode
On-Site (Full-Time)
Experience
3–6 Years
Reports To
Founder / CTO
About grull.spacegrull.space is a proprietary digital asset trading and intelligence firm based in Bangalore. We build advanced systems that aggregate on-chain analytics, derivatives data, social sentiment, market microstructure signals, and smart money flows to generate institutional-grade trading intelligence. Our team combines deep market expertise with technology to gain a decisive information and execution edge in digital asset markets.
About the RoleWe are looking for a Software Engineer to join our core team and take ownership of building, scaling, and maintaining the internal tools and platforms that power our trading and research operations. You will work on-site in close collaboration with our analysts and traders, translating market intelligence requirements into robust, production-grade software.
This is a hands-on, high-impact role. You will own critical systems end-to-end — from data ingestion and normalisation through to scoring engines, alerting pipelines, and user-facing dashboards. As an early engineering hire, you will have significant influence over architecture decisions and technology choices as the firm scales.
What You Will Do- Design, build, and maintain real-time data pipelines that ingest, normalise, and store information from multiple premium data providers via REST, GraphQL, WebSockets, and RPC endpoints.
- Develop and refine internal scoring and signal engines that combine inputs from diverse data layers (on-chain flows, derivatives, social sentiment, tokenomics, market microstructure) into unified, weighted intelligence scores.
- Build event-driven alerting and automation systems — delivering actionable signals via Telegram, Discord, email, and webhook integrations to internal trading desks.
- Collaborate daily with analysts and traders to understand market requirements and translate them into technical features, scoring logic, and dashboard views.
- Review, optimise, and stabilise existing codebases, including work delivered by external vendors — improving performance, reliability, and maintainability.
- Architect and build user-facing dashboards and internal tools for real-time market monitoring, risk assessment, and trade signal visualisation.
- Implement monitoring, logging, error handling, and data integrity checks to ensure system uptime and reliability across all pipelines.
- Contribute to the design of ML and predictive analytics capabilities — anomaly detection, pattern recognition, and predictive scoring models.
- Plan and execute system architecture for multi-user access, role-based permissions, audit trails, and SLA-backed data delivery as the platform scales toward institutional clients.
Must-Have Requirements
- 3–6 years of professional software engineering experience with a strong track record of shipping production systems.
- Proficiency in Python and/or Node.js / TypeScript for backend development and data pipeline work.
- Hands-on experience consuming and orchestrating multiple third-party APIs (REST, GraphQL, WebSockets) at scale with robust error handling and retry logic.
- Solid understanding of data engineering fundamentals: ETL/ELT pipelines, data normalisation, time-series storage, and real-time streaming architectures.
- Experience building event-driven systems, notification pipelines, or alerting engines (Telegram bots, webhook integrations, message queues).
- Familiarity with relational databases (PostgreSQL) and time-series or document stores (TimescaleDB, InfluxDB, MongoDB, or similar).
- Comfort working with cloud infrastructure (AWS, GCP, or equivalent) and containerised deployments (Docker, basic Kubernetes).
- Strong debugging, code review, and system design skills — you will inherit and improve existing codebases as well as build from scratch.
- Excellent communication and collaboration skills — you will work alongside analysts and traders daily, not in isolation.
Good-to-Have (Strong Plus)- Prior experience in digital assets, DeFi, or fintech — understanding of on-chain data, exchange mechanics (DEX/CEX), smart money analytics, or derivatives markets.
- Experience with data science or ML frameworks (scikit-learn, PyTorch, TensorFlow) for anomaly detection, classification, or predictive modelling.
- Familiarity with market data platforms such as Nansen, CoinGlass, Santiment, Dune Analytics, or DeFiLlama.
- Experience building real-time dashboards or data visualisation layers (React, D3.js, Grafana, or similar).
- Knowledge of blockchain data infrastructure: RPC nodes, indexers (The Graph, Goldsky), mempool monitoring tools.
- Background in quantitative finance, trading systems, or proprietary trading firm environments.
Tech Stack & ToolsYou will work with some or all of the following (and help shape the stack as we grow):
Category
Technologies
Languages
Python, TypeScript / Node.js
Data Ingestion
REST, GraphQL, WebSockets, RPC (QuickNode / Alchemy)
Databases
PostgreSQL, TimescaleDB / InfluxDB, Redis
Messaging / Queues
Kafka, RabbitMQ, or AWS SQS
Infrastructure
AWS / GCP, Docker, Kubernetes
Dashboards / UI
React, Next.js, D3.js / Recharts, Grafana
ML / Analytics
scikit-learn, PyTorch, feature stores
Alerting
Telegram Bot API, Discord webhooks, email (SendGrid)
Data Providers
Nansen, CoinGlass, Santiment, Dune, Altfins, DeFiLlama, Kaiko, Amberdata, Glassnode, Cryptoquant, Messari, Coinmarketcap, Alchemy, Tardis, Coin Metrics and Token Terminal
Why Join grull.space- Ground-floor opportunity — shape the technical architecture of an institutional-grade intelligence platform from its earliest stages.
- Direct market impact — the systems you build will directly influence real trading decisions and portfolio outcomes.
- Work alongside domain experts — daily collaboration with experienced digital asset analysts and traders, not just product managers.
- Cutting-edge stack — real-time data engineering, multi-source signal fusion, and ML-based prediction across a challenging and intellectually rewarding problem space.
- Ownership and autonomy — as an early engineering hire, you will have significant influence over technology choices, architecture, and product direction.
- Competitive compensation with performance-linked growth as the firm scales.
Click on Apply to know more.