Shadowfax
Website:
shadowfax.in
Job details:
The context: Shadowfax just closed its most profitable quarter ever. ₹1,358 Cr revenue (+65% YoY), a fifth straight quarter of 60%+ growth, and all-time-high PAT of ₹65 Cr. And AI here is in production, not in slideware: our delivery-partner copilot handles ~16,000 conversations a day with ~97% resolved without human intervention, and Vision AI catches ~40% of mismatched reverse pickups at the doorstep at ~35x lower inference cost than a frontier model.
The CFO's office runs the same way. Agentic reconciliation, LLM-assisted anomaly detection, and self-refreshing dashboards already run our revenue-assurance workflows. We are hiring the engineer who takes this system 10x further.
𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗿𝗼𝗹𝗲
You will be the AI engineer inside Business Finance and Revenue Assurance: one engineer, working with AI, producing the output of a team, at public-company accuracy standards. The systems you build protect revenue across 1 Cr+ shipments a month.
𝗪𝗵𝗮𝘁 𝘆𝗼𝘂'𝗹𝗹 𝗯𝘂𝗶𝗹𝗱
→ Agentic AI workflows (Claude, GPT, or equivalent) that reconcile 1 Cr+ shipments monthly
→ LLM-assisted anomaly detection that flags non-compliance before month close, not after
→ ML models for revenue-leakage and fraud detection: time-series anomaly detection, transaction matching, variance decomposition
→ The finance data layer: SQL/Python ETL pipelines over OMS, TMS, and billing-system extracts, validated and reconciled to source
→ Evaluation harnesses for every AI workflow (golden cases, regression checks) so no unverified number reaches leadership
→ End-to-end reconciliation automation: transaction matching, variance detection, automated settlement workflows
𝗬𝗼𝘂 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗺𝗲𝗮𝘀𝘂𝗿𝗲𝗱 𝗼𝗻
• Rupees recovered and leakage prevented by systems you build
• Hours of manual finance work eliminated
• Accuracy of AI outputs in production: eval pass rates, error budgets
• Speed from leadership question to verified answer
𝗪𝗵𝗼 𝘀𝗵𝗼𝘂𝗹𝗱 𝗮𝗽𝗽𝗹𝘆
• 2-4 years building production ML or AI systems; you have shipped something AI-powered that people actually use
• Proficiency in machine learning and pattern recognition, including designing, training, and evaluating models for complex business problems; NLP for document understanding and query-based analytics
• Expert Python plus deployment (FastAPI, Docker); advanced SQL and feature engineering
• Hands-on LLM work: Claude / GPT / Gemini APIs, prompt engineering, RAG, agentic workflows or MCP
• B.Tech / M.Tech in CS, Data Science, or AI-ML
• Logistics, fintech, or high-volume transactional domain experience preferred
• Accuracy obsession: an unverified number is a defect, not a draft
𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗻𝗼𝘁
• Not AI research: this is applied AI on live financial data, judged by rupees recovered and hours saved
• Not a support seat: you own systems end to end, from pipeline to production to evaluation
• Not a prompt-only role: you ship code that runs unattended
𝗪𝗵𝘆 𝗷𝗼𝗶𝗻
• Build agentic AI in mission-critical finance at a listed company, with real P&L data from day one
• Direct CXO exposure: your systems feed pricing, margin, and commercial decisions at the leadership table
• A team already operating AI-first, where the path from Associate to Director has been walked in two years
𝗖𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗶𝗼𝗻: Competitive CTC, benchmarked to top quartile. Fixed plus performance variable.
#Hiring #AIEngineer #MachineLearning #BusinessFinance #Bangalore #Shadowfax
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