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Quality Assurance Engineer – AI Agentic Applications, AVP

Deutsche BankBank / NBFC

✓ Verified at sourcePosted 33d ago
Location
Pune, Maharashtra
Experience
1–2 yrs
Type
Full time
Work mode
Not stated
Qualification
Not stated
Salary
Not disclosed by employer

You will own quality validation for AI agentic applications from development through production. The work covers LLM accuracy, RAG source attribution, agent behaviour under failure, AI safety testing, and the quality metrics that gate each release.

About this role

Quality Assurance Engineer – AI Agentic Applications, AVP is a full-time Audit & Assurance role at Deutsche Bank, a bank / NBFC, based in Pune. The posting asks for 1–2 yrs of experience. FitRole found it on the employer's own careers site or job board and last confirmed it was live on 11 Nov 2026.

What you'll do

  • Design, run, and maintain test strategies and automation frameworks for AI-powered agentic workflows
  • Test LLM response accuracy, relevance, and grounding, and surface hallucinations and edge-case behaviour
  • Evaluate how autonomous and semi-autonomous agents plan, select and sequence tools, and recover from errors or timeouts
  • Validate RAG pipelines across ingestion, chunking, metadata, embeddings, and citation accuracy
  • Probe for prompt injection, data leakage, unauthorised tool use, and privilege escalation
  • Define quantitative evaluation metrics and quality gates, and turn production failures into regression tests

What they ask for

  • Bachelor's degree or above in Computer Science, Engineering, Information Technology, or a related field
  • 5+ years of software QA and testing, including test planning and functional, integration, regression, and end-to-end testing
  • 1–2 years of hands-on testing of GenAI, LLM, or agentic AI applications
  • Strong record of building automation frameworks and test utilities, not relying solely on manual tools
  • Strong programming in Java, Kotlin, or Python
  • Working knowledge of LLMs, prompt engineering, RAG, embeddings, vector databases, agent workflows, and tool calling, with hands-on use of evaluation tools such as Langsmith, Langfuse, or Ragas

Good to have

  • Experience testing REST APIs, data integrations, and messaging systems such as Kafka
  • Experience in financial services, such as regulatory reporting, reconciliations, or trade lifecycles

Skills mentioned

Reconciliation
Full job description as posted

Job Description:

Job Title: Quality Assurance Engineer – AI Agentic Applications

Location: Pune, India

Corporate Title: AVP

Role Description

Quality Assurance Engineer to validate AI agentic applications across development and production. The position combines specialized AI testing, automation, safety evaluation, and continuous quality measurement. The engineer is responsible to design, build and execute the test strategy for LLM accuracy, RAG ingestion and attribution, agent planning and tool use, recovery behavior, and production failure patterns

What we’ll offer you

As part of our flexible scheme, here are just some of the benefits that you’ll enjoy

  • Best in class leave policy
  • Gender neutral parental leaves
  • 100% reimbursement under childcare assistance benefit (gender neutral)
  • Sponsorship for Industry relevant certifications and education
  • Employee Assistance Program for you and your family members
  • Comprehensive Hospitalization Insurance for you and your dependents
  • Accident and Term life Insurance
  • Complementary Health screening for 35 yrs. and above

Your key responsibilities

  • Design, execute, and maintain test strategies and automation frameworks for AI-powered agentic workflows
  • Develop and implement specialized testing approaches for LLM-powered applications, validating response accuracy, relevance, and grounding, while identifying hallucinations and edge-case behaviours
  • Test and evaluate the behaviour of autonomous and semi-autonomous AI agents, ensuring proper planning, tool selection/sequencing, agent-to-agent interactions, and graceful error/timeout recovery
  • Validate Retrieval-Augmented Generation (RAG) performance, including document ingestion, chunking, metadata quality, embedding accuracy, and citation/source attribution
  • Perform AI safety and security testing to identify vulnerabilities such as prompt injection (direct/indirect), data leakage, unauthorized tool execution, and privilege escalation
  • Establish quantitative AI evaluation metrics and quality gates (e.g., classification accuracy, groundedness, hallucination rate, tool-selection accuracy, and cost/latency) to measure performance across releases
  • Build and maintain automated test suites (covering APIs, UI, integration, RAG, and agent trajectories) to progressively transition the testing suite toward automated continuous evaluation
  • Analyze production AI interactions and failed agent journeys to identify recurring failure patterns, create regression tests from production incidents, and ensure decision auditability

Your skills and experience

Minimum Required Skills & Experience (Must Have):

  • Bachelor's degree or above in Computer Science, Engineering, Information Technology, or a related discipline
  • 5+ years of experience in software quality assurance and testing, with strong knowledge of test planning, functional, integration, regression, and end-to-end testing
  • 1–2 years of hands-on experience specifically testing GenAI, LLM, or Agentic AI applications
  • Strong experience with test automation and building automation frameworks and test utilities (rather than relying solely on manual tools)
  • Strong programming ability in at least one language: Java / Kotlin or Python
  • Strong understanding of generative AI technologies, including LLMs, prompt engineering, RAG, embeddings, vector databases, AI agents/agentic workflows, and tool/function calling
  • Hands-on experience with LLM and agent evaluation tools such as Langsmith/Langfuse, Ragas, or equivalent frameworks for dataset-based testing, custom evaluation metrics, experiment tracking, tracing, and continuous regression evaluation

Add On Experience (Nice to Have):

  • Experience testing API and data integrations, including REST APIs, JSON, SQL, databases, and messaging systems like Kafka
  • Good understanding of CI/CD integration and establishing automated quality gates
  • Experience working in the financial services industry, with knowledge of regulatory reporting, trade lifecycles, transaction reporting, reconciliations, and regulatory controls
  • Experience with AI/LLM orchestration frameworks such as Lang Chain, Lang Graph, Llama Index, Vertex AI, OpenAI, or similar technologies
  • Hands-on experience with advanced AI testing capabilities such as prompt injection testing, AI evaluation/evals, and AI observability
  • Experience testing distributed systems

Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.

How we’ll support you

  • Training and development to help you excel in your career
  • Coaching and support from experts in your team
  • A culture of continuous learning to aid progression
  • A range of flexible benefits that you can tailor to suit your needs

About us and our teams

Please visit our company website for further information:

https://www.db.com/company/company.html

We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.

Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.

We welcome applications from all people and promote a positive, fair and inclusive work environment.

How to apply

You apply on Deutsche Bank's own careers page. FitRole never forwards your CV and never asks for fees.

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