AI Engineer- Traded Risk

Location: 

Bangalore, KA, IN, 560103


Brand:  HSBC
Area of Interest: 
Closing Date:  Hybrid Worker
Date:  18 Sept 2026

Job description

Some careers shine brighter than others.

If you’re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further.

HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.

We are currently seeking an experienced professional to join our team in the role of AI Engineer- Traded Risk (FTC role)

In this role, you will:

  • Activities undertaken include, but not limited to the following: for each team within TRMMC:Design and implement single-agent and simple multi-agent workflows using frameworks such as LangGraph, LangChain, AutoGen, CrewAI, etc.
  • Rapid Prototyping & End-to-End Development: Lead the end-to-end development of Agentic AI applications, from ideation and data exploration to rapid prototyping and initial deployment.
  • Build and maintain tool integrations (function calling / MCP servers) connecting LLM agents to internal risk systems
  • Implement RAG (retrieval-augmented generation) pipelines over risk policy documents, regulatory guidance, and historical incident logs to ground agent outputs in verified sources.
  • Write and iterate on prompt templates, system instructions, and few-shot examples, and maintain a versioned prompt library.
  • Build evaluation harnesses to test agent accuracy, hallucination rate, and task completion, using both automated metrics and structured human review.
  • Implement guardrails: input/output validation, PII and confidential-data filtering, approval checkpoints for any agent action with financial or regulatory consequence.
  • Support human-in-the-loop design — ensuring every agentic workflow has a clear escalation path when confidence is low or an anomaly is detected.
  • Monitor deployed agents in production: track cost (token usage), latency, failure modes, and drift in output quality over time.
  • Document workflows, decision logic, and control points clearly enough for audit and model-risk review.
  • Collaborate with market risk SMEs to translate manual, judgment-heavy processes into structured agent tasks

To be successful you will:

  • Working proficiency in Python, including API integration, async programming, and data manipulation (pandas/numpy).
  • Hands-on experience building agentic applications — this can come from personal projects, hackathons, internships, or professional work.
  • Practical exposure to at least one agent orchestration framework (LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel) or direct experience with the Claude/OpenAI/Gemini APIs including function calling and tool use.
  • Understanding of prompt engineering fundamentals: system prompts, chain-of-thought/structured reasoning prompts, few-shot examples, output formatting (JSON schemas, XML tags).
  • Familiarity with RAG architectures: embeddings, vector databases (e.g., Pinecone, Weaviate, FAISS, pgvector), chunking strategies, and retrieval evaluation.
  • Basic understanding of LLM evaluation techniques — golden datasets, LLM-as-judge patterns, regression testing for prompt changes.Foundational understanding of market risk concepts — VaR, Greeks, stress testing, limit frameworks — gained through coursework, self-study, or prior exposure.
  • FRM Part I/II, CQF, or equivalent certification in progress or completed.Experience with MCP (Model Context Protocol) server development for tool integration.
  • Exposure to model risk management (MRM) or SR 11-7-style validation frameworks.
  • Prior experience in a regulated environment (banking, insurance, asset management).
  • A background in software engineering, data engineering, or quant development, given the technical build nature of this role.Interns can also be considered with 1 year of exposure in AI.


You’ll achieve more at HSBC 

hsbc.com/careers

HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.”

 

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