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Head of Applied AI & Trading Systems (Iron Man Track)

Deeter Analytics · Ghar se kaam
SeniorGhar se kaam
PagaarPagaar nahi likha
KahanGhar se kaam
TypeFull timeDirector, Executive
Posted19 Sep24 din pehle, Himalayas se
Jo skills maange hain7 likhe hain
Senior Trading Systems EngineerSenior Trading Technology EngineerTrading Technology Team LeadApplied AI LeadTrading Strategy LeadHead Of AI EngineeringHead Of AI Development
Is job ke baare mein

The Gist

Deeter Analytics is a private investment firm managing approximately $500M across public markets, alternatives, and private investments.

We are small, profitable, and aggressive.

We don’t have committees. We have capital, judgment, and a need for speed.

We are hiring a technical builder to sit directly beside the CIO and architect the firm’s intelligence layer — the system that determines how we see the market.

This is not a quant role.

This is not a reporting role.

This is not a research-for-research’s-sake role.

This is a Human-in-the-Loop AI role: building the Iron Man suit — an exoskeleton that allows a human trader to process 100× more information without losing intuition, discretion, or speed.

This role sits at the center of our trading advantage.

The Problem

Markets are noisy. Alpha comes from synthesis.

We already have access to the data.

The bottleneck is human bandwidth.

Too much time is spent

Refreshing feeds

Reading things that don’t matter

Manually stitching together signal across sources

Latency kills insight. Insight kills latency.

The Mission

Build the nervous system of the firm.

You will own the entire loop

Ingestion → LLM synthesis → Trader decision

Your mandate is simple and brutal

Reduce time-to-insight across the entire trading operation.

If you surface a signal 10 minutes faster than the street, we win.

If you automate away four hours of reading, we double our capacity.

What You Will Own

Information Pipelines (Kill the “F5” Key)

You will design and maintain automated pipelines that ingest, clean, and normalize

News, filings, earnings calls, macro releases

Social and sentiment data

Alternative and proprietary datasets

Your job is to replace manual refresh workflows with push-based alerts that surface only what matters — mapped directly to

Watchlists

Live positions

Risk exposure

Reliability matters. Latency matters. Silence matters.

2. AI-Augmented Research (A Live Analyst on the Desk)

You will deploy LLM-powered systems to summarize, extract, compare, and reason over

10-Ks, 10-Qs, earnings calls, central bank minutes

Sell-side research and internal notes

You will build “chat with our data” tools that allow traders to query proprietary research in natural language.

Example

“Summarize the bear case from the last three earnings calls.”

You will also create tools for fast discretionary back-testing

“How did this asset behave during the last three macro shocks of this type?”

Signal & Noise Filtering (Protect Attention)

You will build the filters that decide what breaks through.

Sentiment and relevance scoring

Entity recognition that maps events to exposure

Dashboards that surface regimes, anomalies, and dislocations — not vanity metrics

If something matters, it should scream.

If it doesn’t, it should disappear.

  • Infrastructure, Security & Reliability (Own the Stack)

You own the compute layer that runs the intelligence system.

Cloud and/or local GPU infrastructure

Vector databases and retrieval systems

Data-privacy-first architectures (local models where required)

You choose the architecture.

You ship what runs fastest and breaks least.

Our proprietary data and strategies do not leak. Ever.

Who You Are

You Are a Founder-Hacker

You have likely

Built your own projects

Traded your own account

Worked in a high-stakes startup, prop shop, or family office

You hate waiting for permission.

You like tools that get used today.

You Speak Python

Python (Pandas, NumPy) is non-negotiable

You have hands-on experience with

LLMs and RAG architectures

Prompting, evaluation, and failure modes

Vector databases (Pinecone, Milvus, FAISS, etc.)

Orchestration (LangChain, Airflow, or custom agents)

REST & WebSocket APIs (market data, news, internal tools)

Lightweight internal UIs (Streamlit, Dash, Retool, etc.)

You know the difference between an LLM demo and a production system.

You care about latency, hallucinations, and context windows.

You Get Markets (Enough)

You don’t need to be a portfolio manager — but you understand that

Financial data is messy, adversarial, and time-sensitive

Narratives are not facts

A 10-K is not a blog post

You are comfortable making judgment calls under uncertainty.

The Deeter Mindset

Co-Ownership Mentality

This is not a role for staff augmentation or support work. We are looking for a technical partner who thinks in outcomes, edge, and shared P&L — and wants to win in a competitive, adversarial market.

We optimize for people who value

Pragmatism over theory

You ship things that work by market open — not in six months.

Discretionary empathy

Human judgment is the final decision engine.

Your systems amplify it; they do not replace it.

Founder-level ownership

You treat this system like your P&L depends on it — because it does.

Why This Role

Zero Latency

You sit with the decision-makers. You push code. We use it the same day.

Real Impact

You are not optimizing ad clicks. You are building the intelligence engine for a $500M portfolio.

Sovereignty

No middle management. No reporting theater. Just results.

To Apply

Do not send a cover letter.

Send

A GitHub

A project you’re proud of

Or a short note on how you would architect a real-time news filter for a trading desk

We care about how you think and what you build.

Originally posted on Himalayas

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