Data Scientist

Role & responsibilities

Job Title:  Senior Data Scientist
Location:  BangaloreBusiness & Team: BB Advanced Analytics and Artificial Intelligence COEImpact & contribution:As a Senior Data Scientist, you will be instrumental in pioneering GenAI and multi-agenticsystems at scale within CommBank. You will architect, build, and operationalize advancedgenerative AI solutionsleveraging large language models (LLMs), collaborative agenticframeworks, and state-of-the-art toolchains. You will drive innovation, helping set theorganizational strategy for advanced AI, multi-agent collaboration, and responsible next-genmodel deployment.Roles & Responsibilities:• GenAI Solution Development:Lead end-to-end development, fine-tuning, and evaluation of state-of-the-art LLMsand multi-modal generative models (e.g., transformers, GANs, VAEs, DiffusionModels) tailored for financial domains.• Multi-Agentic System Engineering:Architect, implement, and optimize multi-agent systems, enabling swarms of AIagents (utilizing frameworks like Langchain, Langgraph, and MCP) to dynamicallycollaborate, chain, reason, critique, and autonomously execute tasks.• LLM-Backed Application Design:Develop robust, scalable GenAI-powered APIs and agent workflows using FastAPI,Semantic Kernel, and orchestration tools. Integrate observability and evaluationusing Langfuse for tracing, analytics, and prompt/response feedback loops.• Guardrails & Responsible AI:Employ frameworks like Guardrails AI to enforce robust safety, compliance, andreliability in LLM deployments. Establish programmatic checks for prompt injections,hallucinations, and output boundaries.• Enterprise-Grade Deployment:Productionize and manage at-scale GenAI and agent systems with cloudinfrastructure (GCP/AWS/Azure), utilizing model optimization (quantization, pruning,knowledge distillation) for latency/throughput tradeoffs.• Toolchain Innovation:Leverage and contribute to open source projects in the GenAI ecosystem (e.g.,LangChain, LangGraph, Semantic Kernel, Langfuse, Huggingface, FastAPI).Continuously experiment with emerging frameworks and research.• Stakeholder Collaboration:

Partner with product, engineering, and business teams to define high-impact use
cases for GenAI and agentic automation; communicate actionable technicalstrategies and drive proof-of-value experiments into production.• Mentorship & Thought Leadership:Guide junior team members in best practices for GenAI, prompt engineering, agenticorchestration, responsible deployment, and continuous learning. RepresentCommBank in the broader AI community through papers, patents, talks, and open-source.Essential Skills:• 10+ years of hands-on experience in Machine Learning, Deep Learning, orGenerative AI domains, including practical expertise with LLMs, multi-agentframeworks, and prompt engineering.• Proficient in building and scaling multi-agent AI systems using LangChain,LangGraph, Semantic Kernel, MCP, or similar agentic orchestration tools.• Advanced experience developing and deploying GenAI APIs using FastAPI;operational familiarity with Langfuse for LLM evaluation, tracing, and error analytics.• Demonstrated ability to apply Guardrails to enforce model safety, explainability, andcompliance in production environments.• Experience with transformer architectures (BERT/GPT, etc.), fine-tuning LLMs, andmodel optimization (distillation/quantization/pruning).• Strong software engineering background (Python), with experience in enterprise-grade codebases and cloud-native AI deployments.• Experience integrating open and commercial LLM APIs and building retrieval-augmented generation (RAG) pipelines.• Exposure to agent-based reinforcement learning, agent simulation, and swarm-basedcollaborative AI.• Familiarity with robust experimentation using tools like LangSmith, GitHub Copilot,and experiment tracking systems.• Proven track record of driving GenAI innovation and adoption in cross-functionalteams.

Education Qualifications: Bachelor’s or Master’s degree in Computer Science,
Engineering, Information Technology, or a related technical discipline.Desirable:• Papers, patents, or open-source contributions to the GenAI/LLM/Agentic AIecosystem.• Experience with financial services or regulated industries for secure and responsibledeployment of AI.