01
OCT 2025 — PRESENT
NEW YORK
Hypha↗
Engineering Manager
/ AI systems & engineering leadership
Turning fragmented financial documents into intelligence that
people can act on.
I lead a team of eight engineers and stay hands-on across the
agent platform, document intelligence, and evaluation
infrastructure. The work supports credit and asset-management
teams through covenant analysis, credit memos, lender
narratives, and financial spreading.
PDFXLSMAIL
Context
Cited
intelligence ↗
DOCUMENTS → ENTITIES → ANALYSIS
2M+
structured attribute values
50K+
production documents
What I built & how +
A reusable agent platform
Isolated E2B execution, pluggable Claude and OpenAI
runtimes, permission-scoped MCP tools, durable state, and
skills. One foundation for interactive analysis and
background financial workflows.
An operational knowledge graph
Configurable entities, relationships, attributes, source
rules, and computed entities. Agents, analytics, and
automation work from the same model of a customer’s
business.
Quality beyond a demo
Retry-safe ingestion across PDFs, Excel, and email. Cited,
versioned writes. Langfuse evaluations, regression
datasets, and Axiom monitoring to check grounding and
workflow reliability.
Agent runtimesKnowledge graphsEvaluationLeadership
02
JUN 2024 — OCT 2025
NEW YORK
AgentSmyth↗
Staff AI Engineer
/ Early team, platform architecture
From employee #2 to enterprise financial intelligence.
I joined at the beginning and led technical strategy as the
product grew into a production multi-agent platform. I built
systems that combined market data, earnings transcripts,
retrieval, and financial reasoning to produce fully cited
research and portfolio insights.
Market dataEarnings calls100+ sources
MacroQuantOptionsSentiment
↳ Cited financial research
What I built & how +
Specialized agents, shared infrastructure
Autonomous macro, quantitative, options, and sentiment
agents using OpenAI, Anthropic, Gemini, and Perplexity.
Retrieval through Pinecone and LlamaIndex across more than
100 financial data sources.
Built to reach enterprise users
Distributed orchestration on AWS Lambda and SQS,
event-driven processing, and both SaaS and on-premises
deployments. I contributed across architecture, customer
deployments, roadmap, and engineering execution.
A company milestone
Helped scale the business to $1M ARR and help secure $9.1M
in funding. A team outcome, with my contribution centered
on technical strategy and implementation.
Multi-agent systemsFinancial researchAWS0 → 1
03
NOV 2021 — JUN 2024
NEW YORK
S&P Global↗
Data Scientist → Senior Data Scientist
/ Market Intelligence
Machine learning at the scale of global finance.
I built credit-risk models and a cloud scoring platform for
unrated issuers, then expanded into document intelligence,
retrieval-based analytics, ESG forecasting, and
investment-banking automation.
30K+
unrated issuers covered
99%
efficiency gain in scoring
$1.2M
annual revenue impact
What I built & how +
Credit risk, on demand
Python-based models and AWS infrastructure to scale issuer
scoring. The result extended coverage while reducing
manual work.
From financial text to analyst workflows
LLM summarization and topic modeling for Capital IQ Pro,
retrieval-augmented analytics APIs, and transformer-based
analysis of SEC climate disclosures. Separate
document-intelligence work identified $6.8M in revenue
potential. I also automated Public Information Book
generation for investment-banking teams.
Recognition
Rising Star Award as a Data Scientist; Brand Ambassador
Award as a Senior Data Scientist.
Credit-risk modelingNLPRAGPython
04
2017 — 2021
PAKISTAN → EUROPE
The foundations↗
Software first. Then data. Then a deeper study of intelligence.
2021
BMW Group
Data Scientist · Internship
MAR — AUG 2021 / MUNICH, GERMANY
2020
Setai
Data Science Consultant · Contract
AUG 2020 — FEB 2021 / BOLOGNA, ITALY
2019
Packages Group
Data Engineer
JAN — NOV 2019 / LAHORE, PAKISTAN
2017
Fatima Group
Software Engineer
OCT 2017 — OCT 2018 / PAKISTAN
View my full experience ↗
