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Accolite
ob Summary:
We are looking for an experienced Senior AI Developer with strong expertise in Agentic AI systems, Large Language Models (LLMs), and Data Engineering.
The ideal candidate will design and build intelligent multi-agent systems capable of data discovery, retrieval, reasoning, and enrichment across diverse enterprise data sources. This role combines AI model development, data orchestration, and integration of LLM-powered pipelines for financial analytics and automation.
Key Responsibilities:
AI Agent Development:
Design and build multi-agent AI systems capable of orchestrating data discovery, retrieval, and enrichment across databases, APIs, documents, and trading systems.
Data Orchestration & Integration:
Build data pipelines to consolidate and refresh time-series, trade, risk, and market data from structured and unstructured sources (e.g., SQL, REST APIs, CSV, data marts).
Portfolio Analytics Framework:
Develop analytics modules to compute P&L, VaR, exposure, and performance metrics across multiple asset classes.
Automate reporting and dashboard updates through AI-driven workflows.
Autonomous Reasoning & Planning:
Leverage frameworks such as LangChain, CrewAI, AutoGen, or Semantic Kernel for autonomous task orchestration (e.g., identifying stale data, refreshing missing datasets, triggering recalculations).
LLM & Retrieval-Augmented Generation (RAG):
Implement RAG pipelines and vector databases to enable natural-language portfolio queries and generate human-readable insights using LLMs (GPT, Claude, Llama, etc.).
Core Competencies:
AI/Agentic Expertise:
Strong hands-on experience with LangChain, CrewAI, AutoGen, or similar multi-agent frameworks.
Proven track record in building autonomous AI copilots or orchestration systems.
Data Engineering Proficiency:
Solid understanding of Python, SQL, APIs, and data integration frameworks (e.g., Airflow, dbt, PySpark).
Exposure to financial data domains such as positions, trades, and risk sensitivities.
Machine Learning & NLP:
Experience with LLMs (GPT, Claude, Llama, etc.), embeddings, and vector search (Pinecone, FAISS, Chroma).
Ability to design RAG, summarization, and contextual reasoning pipelines for structured/unstructured data.
Required Qualifications:
Bachelor’s or Master’s degree in Computer Science, AI, or a related technical field.
8+ years of experience in AI / ML development and data engineering.
Strong programming skills in Python.
Proficiency in LLM integration, data orchestration, and API development.
Understanding of cloud deployment, MLOps, and AI workflow automation.
Preferred Skills:
Knowledge of financial data systems or quantitative analytics.
Familiarity with Docker, Kubernetes, and CI/CD for AI pipelines.
Understanding of vector databases and semantic search.
Experience in building AI copilots or multi-agent systems for enterprise use.
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