Position: Python Developer
Location: Hybrid/ NYC
Contract: 1-2 Years
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
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