Python Developer/AI Engineer/Capital Markets/Trading
Required
Candidate Location: Hybrid/ NYC 3 days a week - NO RELOCATION
**** CANDIDATES MUST HAVE RECENT LOCAL PROJECTS IN THE NY/NJ AREA.
Type of Interview Required:
Video
***
Experience required on a resume and for submittal:
1. How many years working with:
AI Engineer
2. How many years working with:
Python
3. How many years working with: AI/ML or LLM-based applications and prototypes
4. How many years working with:
Capital Markets/Trading
5. How many years working with: Jupyter, Pandas, NumPy, LangChain, and cloud AI services (AWS/Azure/OpenAI)
Job Description:
Seeking a
hands-on AI Engineer/Developer
to rapidly prototype and deliver AI-driven solutions across investment, research, and trading functions. This role is ideal for someone who can bridge
financial domain knowledge with applied AI/ML development , building proof-of-concepts that can evolve into production-grade tools supporting investment decision-making.
Key Responsibilities
Design and develop
AI/ML prototypes
using Python to support investment research, portfolio analytics, and trading insights
Build and test
LLM-based and data-driven use cases
(e.g., research summarization, signal generation, document analysis, automation)
Work closely with
investment professionals, research teams, and data engineers
to translate business needs into functional AI solutions
Develop and integrate
data pipelines, APIs, and analytical models
to support rapid experimentation
Leverage tools such as
Jupyter, Pandas, NumPy, LangChain, and cloud AI services (AWS/Azure/OpenAI)
Perform
data exploration, feature engineering, and model validation
on financial datasets
Iterate quickly on prototypes, incorporating feedback to refine models and outputs
Ensure solutions consider
data security, governance, and compliance
within a financial services environment
Required Qualifications
10+ years of experience in
Python development
with strong hands-on coding ability
Experience building
AI/ML or LLM-based applications and prototypes
Exposure to
financial services, asset management, trading, or investment research
Strong experience with
data analysis libraries
(Pandas, NumPy) and working with structured/unstructured data
Familiarity with
APIs, microservices, and cloud platforms (AWS, Azure, or GCP)
Ability to work in a
fast-paced, iterative environment
with direct interaction with business stakeholders
Preferred Qualifications
Experience with
LLM frameworks
(LangChain, RAG architectures, vector databases)
Knowledge of
financial data sets, market data, or portfolio analytics
Experience prototyping tools for
quant research, credit analysis, or trading workflows
Familiarity with
Snowflake, Databricks, or modern data platforms
What Success Looks Like
Rapid delivery of
high-impact AI prototypes
that demonstrate clear business value
Strong collaboration with front-office teams to
solve real investment and research problems
Ability to evolve prototypes into scalable solutions in partnership with engineering teams