AI Engineer

IDFC FIRST Bank · Bengaluru

  • Experience3–8 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelmid
  • Posted2 Sept 2026
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About IDFC FIRST Bank

IDFC FIRST Bank is hiring in Bengaluru in financial services. This role looks for around 3+ years of experience.

Skills

  • Generative AI
  • Retrieval-Augmented Generation
  • Large Language Models
  • PEFT
  • LLMOps
  • AWS
  • Azure
  • Docker
  • Kubernetes
  • CI/CD
  • NLP
  • Computer Vision
  • Multimodal AI
  • Spark
  • Airflow

The role

An AI engineer in banking develops generative AI applications for financial operations and customer service, architecting Retrieval-Augmented Generation pipelines and fine-tuning large language models with PEFT techniques. They deploy scalable models and backend services through LLMOps, AWS or Azure, Docker, and Kubernetes while integrating secure AI systems into enterprise platforms. Their skills include generative AI, Retrieval-Augmented Generation, large language model fine-tuning, PEFT, LLMOps, cloud deployment, Docker, and Kubernetes.

Full job description

We are seeking an AI Engineer with 3-8 years of experience to design, build, and deploy end-to-end AI solutions with a focus on Generative AI (GenAI), Retrieval-Augmented Generation (RAG) pipelines, copilots, and applied AI systems that deliver measurable business impact. The role involves architecting scalable AI platforms, fine-tuning large language models (LLMs) using PEFT techniques (LoRA, QLoRA, Unsloth), and building LLM Ops pipelines for model lifecycle management. The ideal candidate combines AI engineering, MLOps, and cloud expertise, with experience across NLP, computer vision, and multimodal AI, and a strong ability to deliver enterprise-grade AI solutions for banking.

The core responsibilities for the job include the following:

Primary:

Build and deploy AI-powered applications(chatbots, copilots, automation flows) for banking operations and customer service.

Design and implement RAG pipelines and AI agents for secure financial data insights.

Fine-tune and optimize LLMs using LoRA, QLoRA, and other PEFT techniques.

Develop end-to-end LLMOps pipelines(training, evaluation, deployment, monitoring).

Expose backend APIs/microservices to integrate LLMs into banking platforms.

Deploy scalable AI models on AWS/Azure with Docker, Kubernetes, CI/CD, while ensuring security and compliance.

Secondary:

Collaborate with product managers, data scientists, and compliance teams to translate business needs into AI solutions.

Create reusable AI components, SDKs, and templates for faster adoption.

Support data engineering pipelines(ETL/ELT, Spark, Airflow).

ConductA/B testingand feedback collection for continuous model improvement.

Explore emerging GenAI tools, open-source models, and fine-tuning strategies.

Managerial/Leadership:

Mentor and lead a team of AI engineers, promoting best practices in LLMOps and GenAI.

Drive cross-functional collaboration to align AI solutions with business goals.

Oversee project delivery, resource planning, and ensure quality standards.

Key Success Metrics:

Improved accuracy and performance of domain-specific AI models.

Reliable and frequent AI deployments with minimal downtime.

Low-latency and high throughput for customer-facing systems.

Reduction in infrastructure and operational costs via PEFT.

99.9%+ uptime of production AI services.

Early detection of model drift and anomalies.

Tangible business impact(e. g., faster service, better fraud detection).

Strong compliance with security and regulatory frameworks.

High adoption of AI components across teams.

Requirements:

Experience: 3-8 years in AI/ML Engineering, with exposure to LLMs, MLOps, and GenAI projects.

Graduate: Bachelor's or Master's in Computer Science, Data Science, or related field.