Company Overview

As a leading global professional services firm, we sit at the intersection of strategy, technology, and industry expertise. Our Advisory practice partners with the worlds most influential financial institutions to solve their most complex challenges. We are currently expanding our AI & Data Engineering powerhouse to support Global Capability Centers (GCCs) in the Banking, Financial Services (BFS) sector. We don’t just advise; we build, deploy, and scale the future of intelligent finance.

Role Context The Forward Deployed AI Engineer (FDE) is a high-impact, hybrid role that bridges the gap between deep technical engineering and strategic business consulting. Unlike traditional backend engineers, you will be embedded directly with our BFSI GCC clients, working on the front lines to productionize Generative AI solutions. You will be responsible for moving AI from "proof of concept" to "industrial-grade" within highly regulated environments, ensuring that every model deployed creates measurable alpha or operational efficiency.

Key Responsibilities

- Rapid Prototyping & Deployment: Design and build production-ready AI applications, moving from initial client requirements to MVP in weeks, not months.
- Architecture Design: Develop scalable RAG (Retrieval-Augmented Generation) architectures and multi-agent systems tailored for complex BFSI datasets.
- Client Integration: Work on-site at client GCCs to integrate AI solutions into existing legacy infrastructures and contemporary cloud environments.
- Stakeholder Management: Translate complex technical AI concepts into business value for C-suite stakeholders and functional heads.
- Operational Excellence:



Ensure all AI deployments meet the rigorous security, latency, and reliability standards required by global financial institutions.

Technical Qualifications Generative AI & DevOps
- Deep experience with Large Language Models (LLMs) including GPT-4, Claude, and Llama, with a focus on fine-tuning and prompt engineering, guardrails.
- Proven ability to build Autonomous Agents and multi-agent orchestrations using frameworks like LangChain, LangGraph, CrewAI, or AutoGen.
- Expertise in building and optimizing RAG pipelines using Vector Databases such as Pinecone, Weaviate, or Milvus.
- Proficiency in Python and modern AI frameworks (PyTorch, TensorFlow), MCP integration.
- Experience designing "human-in-the-loop" systems for complex decision-making processes.
- Experience with API design and integration (REST, GraphQL) to connect AI agents with core banking systems.
- Strong hands-on experience with Azure or AWS or GCP, including containerization, CI/CD, Kubernetes, Helm charts and production deployment of scalable AI applications.

Domain Qualifications: BFSI
- Experience working with core banking systems, payment gateways, or high-throughput financial ledgers, with working knowledge of BFSI regulatory and compliance considerations. Expert-level knowledge of handling PII (Personally Identifiable Information) and implementing data masking within AI workflows.

Leadership & Communication: Strong stakeholder communication skills with the ability to mentor engineers and translate business goals into scalable, measurable AI solutions. Also ability to translate business requirement to technical implementation.

📌 Forward Deployed AI Engineer (Bengaluru)
🏢 PwC India
📍 Bengaluru