GenAI Platform Engineer (Python, MCP & Agentic AI)
About The Position
We are seeking a highly skilled GenAI Platform Engineer to design, develop, and scale next-generation AI-powered solutions that support investment banking and financial services workflows. This role will focus on building enterprise-grade Generative AI platforms, agentic workflows, Model Context Protocol (MCP) integrations, Retrieval-Augmented Generation (RAG) capabilities, and secure backend services that enable business users to leverage AI solutions in a controlled, governed, and production-ready environment. The ideal candidate will have deep expertise in Python, GenAI architectures, LLM orchestration frameworks, MCP implementations, API development, cloud-native services, and financial data integrations.
Requirements
- Bachelor's degree in Computer Science, Engineering, AI, or a related technical field (or equivalent experience).
- Strong hands-on experience with Python backend development.
- Proven experience building GenAI applications, LLM workflows, agentic systems, or AI-powered platforms.
- Experience with MCP concepts and implementations, including tools, resources, servers, and clients.
- Experience with LangChain, LangGraph, or similar orchestration frameworks.
- Strong understanding of RAG, embeddings, vector search, retrieval quality, and grounding techniques.
- Experience developing APIs using FastAPI, REST, and async Python.
- Knowledge of Git, CI/CD, testing frameworks, and cloud deployment practices.
- Experience with AWS and containerized applications.
- Understanding of enterprise security, authentication, authorization, and secrets management.
- Experience in banking, financial services, capital markets, or other regulated environments preferred.
Nice To Haves
- Experience with AWS Bedrock, Claude models, and managed GenAI services.
- Experience integrating FactSet, Bloomberg, S&P Capital IQ, Refinitiv, Fitch, or similar data providers.
- Knowledge of OpenSearch, Pinecone, pgVector, Weaviate, Chroma, or other vector databases.
- Familiarity with OpenTelemetry, observability, AI evaluation frameworks, and prompt management.
- Understanding of AI governance, model risk management, data privacy, and regulatory controls.
- Exposure to investment banking workflows including IPOs, ECM, DCM, M&A, and advisory processes.
Responsibilities
- Design, develop, and maintain Python-based GenAI services, agent workflows, MCP integrations, and reusable platform components.
- Build MCP servers, clients, tools, resources, prompts, schemas, and authorization frameworks.
- Develop agent orchestration workflows including tool calling, function calling, retrieval, workflow execution, and output generation.
- Design and implement RAG pipelines covering ingestion, embeddings, retrieval, ranking, answer synthesis, and citations.
- Integrate internal and external data sources, including financial data providers, SEC filings, enterprise repositories, web search, and banking platforms.
- Develop secure, production-grade APIs and backend services using Python, FastAPI, and asynchronous programming.
- Implement authentication, authorization, entitlement controls, logging, monitoring, testing, and model output validation.
- Collaborate with business stakeholders, architects, cloud engineers, and governance teams to deliver production-ready AI solutions.
- Create and maintain technical documentation, architecture designs, and operational procedures.
Benefits
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
