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Director - AI Engineering

Capital One

Full time
Experience
3+ years
Location
Bangalore
Work mode
Not stated
Salary
₹15L – ₹25L a year estimatetypical for IT Jobs in Bangalore, 286 posts
Posted 7 days ago

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Role at a glance

You will
  • Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large…
  • Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters…
  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance. scalability, cost, latency, throughput of…
Experience
3+ years
Must-have skills
AWSGoogle Cloud Platform (GCP)Machine LearningMicrosoft Azure

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Job description

Voyager (94001), India, Bangalore, Karnātaka

Director - AI Engineering

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent along with our deep experience in machine learning, position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. Our Generative AI models and platforms empower teams across Capital One to enhance their products by composing powerful, safe and explainable AI capabilities such as agentic workflows, and shared services such as guardrails, observability and evals coupled with foundational model power of open-weight and proprietary frontier models. The team is also delivering capabilities on top of the platform to optimize the software development life-cycle to dramatically enhance developer productivity and model-development life cycle to improve time-to-market of machine learning models.

In this role, you will:

  • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
  • Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
  • Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch and more.
  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance. scalability, cost, latency, throughput of large scale production AI systems.
  • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
  • Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI.

The Ideal Candidate:
  • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
  • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
  • You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example.
  • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
  • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
  • You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:
  • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field such as Statistics, Economics, Operations Research, Analytics, Mathematics or Engineering
  • At least 3 years of people leadership experience
  • At least 6 years of experience developing AI and ML algorithms or technologies
  • At least 6 years of experience deploying scalable and responsible AI solutions on cloud platforms including AWS, Google Cloud or Azure

Preferred Qualifications:
  • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics or related field
  • 5+ years of experience managing and leading an engineering team
  • 8+ years of experience deploying scalable and responsible AI solutions on cloud platforms including AWS, Google Cloud or Azure
  • 8+ years of experience developing AI and ML algorithms or technologies, such as LLM Inference, Similarity Search and VectorDBs, Guardrails, and Memory.
  • Passion for staying abreast of the latest AI research and AI systems and judiciously apply novel techniques in production
  • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Key skills

Required

AWSGoogle Cloud Platform (GCP)Machine LearningMicrosoft Azure

Soft skills

CommunicationPresentation Skills

About company

Capital One is a nationally recognized and high-tech business banking company, offering better customized consumer and commercial lending and deposit financial services.

Tags

Job market insights

1,162active AWS jobs in Bangalore
691active Google Cloud Platform (GCP) jobs in Bangalore
374active Machine Learning jobs in Bangalore
₹15L – ₹25L advertised yearly salary for IT Jobs in Bangalore (middle half of 286 posts that show a salary; median ₹20L)
18 more open jobs at Capital One

Most IT Jobs posts in Bangalore ask for 3–6 years of experience (41% of 3732 that say).

Hiring most for IT Jobs in Bangalore

  • Bosch Group165 open jobs
  • Trigent Software Private Limited157 open jobs
  • Brillio115 open jobs

Jobs asking for AWS in Bangalore also ask for

  • Microsoft Azure57%
  • Python54%
  • Google Cloud Platform (GCP)49%
  • CI/CD41%
  • Kubernetes38%

From live job posts on CoreHRx, updated 7 Nov 2026. Skill figures count posts that list their skills; salary figures only posts that show a salary.

Questions about this job

What is the salary for this Director - AI Engineering job?

The post does not state the pay. As an estimate, comparable posts on CoreHRx advertise ₹15L – ₹25L a year (typical for IT Jobs in Bangalore, 286 posts).

How much experience does this job need?

The post asks for 3 Yrs experience.

Where is this job based?

In Bangalore.

What kind of job is this?

It is a full time job.

This page is for Indian job seekers preparing for cloud engineer, DevOps, backend and solutions architect roles that list AWS as a skill, whether you are a fresher with a first certification or an experienced engineer moving into a senior role. It covers 60 questions in three levels: core services and concepts, then design and configuration choices for one to three years of experience, and finally scenario, security, cost and troubleshooting questions asked in senior rounds. Read each answer, explain it aloud in your own words, and try the CLI commands in a practice account with a billing alert set.

Questions you may be asked

  1. What is the difference between an AWS Region and an Availability Zone?
  2. Explain the AWS shared responsibility model.
  3. What is Amazon EC2, and how do you read an instance type name like m7g.large?
  4. What is Amazon S3, and what are its main storage classes?

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