Python Angular Fullstack Developer - Assistant Vice President

Citigroup Inc.; Bengaluru; On-site; INR 4,500,000 - 9,000,000; Full time

Job summary

Citigroup Inc. is seeking a senior AI/Analytics engineer to lead end-to-end delivery of AI-powered products. You will design API-first services in Python/Node.js, build intuitive front-end interfaces, and deploy containerized microservices with automated CI/CD.

You will apply GenAI techniques, ensure security and data governance, and work closely with product, data, security, and platform teams to translate ambiguous problems into robust capabilities.

Qualifications

• 8+ years of experience in full stack development and data science (ML/DL).
• Production AI/ML-enabled products shipped in agile environments.
• Strong Python production web apps experience (5+ years).

Responsibilities

• Ideate on analytical projects addressing strategic business priorities.
• Own end-to-end delivery of AI-powered products from requirements to deployment.
• Design and build API-first services (REST/GraphQL) in Python and Node.js.
• Develop front-end interfaces with React/Angular/Vue to operationalize model insights.
• Implement containerized services with Docker and automate CI/CD pipelines.
• Establish secure-by-design practices with authentication/secret management and data access controls.
• Instrument applications with monitoring, logging, and performance tuning.
• Collaborate with product, data, security, and platform teams to prioritise roadmaps.
• Create architecture diagrams and runbooks; participate in code reviews.

Skills

Python

Angular

TypeScript/JavaScript

REST APIs

GraphQL

SQL

NoSQL

Docker

CI/CD

Ansible

Linux/Windows

Security best practices

MLOps / GenAI

Education

Bachelor / Masters in Computer Science Engineering

Tools

Docker

Tekton

Harness

Git

Ansible

Job description

Job Family Group

Decision Management

Job Family

Specialized Analytics (Data Science/Computational Statistics)

Time Type

Full time

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

For complementary skills, please see above.

Good to Have

• Experience with enterprise identity and access management, secrets vaults, and compliance controls.
• Knowledge of data privacy and responsible AI practices; experience implementing audit and guardrail tooling.
• Familiarity with vector databases and search infrastructure.

Education

• Bachelor / Masters (preferred) in Computer Science Engineering.

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

Experience

• Min 8 years of relevant experience in full stack development and Data Science (ML and DL) combined.
• Demonstrated track record shipping AI-enabled products to production in an agile environment.

Must have substantial experience in

• 5+ years, building production web applications and services with Python.
• Front-end development with Angular; strong TypeScript/JavaScript fundamentals.
• API design and development with REST and GraphQL; experience with microservices patterns.
• Datastores: SQL (e.g., PostGREs) and NoSQL (e.g., MongoDB); schema/data modeling, indexing, and performance tuning.
• Containers with Docker; CI/CD using Tekton, Harness, and Git-based pipelines for automated testing and deployments.
• Configuration management and automation with Ansible; scripting for environment provisioning and release management.
• Operating systems: Linux and Windows; solid understanding of OS/process fundamentals.
• Networking basics: DNS, load balancers, firewalls, routing, ports, and protocols.
• Observability: application monitoring, centralized logging, tracing; strong debugging and problem-resolution skills.
• Security: authentication, authorization, secret management, secure coding and dependency hygiene.

Generative AI & Deep Learning (Complementary and Strongly Preferred)

• Hands-on with LLMs and transformer architectures; experience with prompt engineering and system prompt design.
• Retrieval-Augmented Generation (RAG): embeddings, vector indexes, chunking strategies, and retrieval evaluation.
• Model customization: fine-tuning/LoRA/PEFT; data curation, labeling, and experiment tracking for reproducibility.
• Frameworks and tooling: PyTorch/TensorFlow, Hugging Face ecosystem, and popular orchestration libraries.
• Model serving/inference optimization: batching, token streaming, quantization, caching, and concurrency controls.
• Quality & safety: automatic evaluation, red-teaming, toxicity filters, PII handling, prompt injection defenses.
• MLOps for GenAI: feature pipelines, model registries, rollout strategies (A/B, shadow), monitoring for drift and hallucinations.

Responsibilities

• As a key contributor to ideation on analytical projects to tackle strategic business priorities.
• The role will require endless curiosity, as ambiguity and open-ended questions are a core part of the team’s work.
• Own end-to-end delivery of AI-powered products: requirements, design, implementation, testing, deployment, and support.
• Design and build API-first services (REST/GraphQL) in Python and Node.js that expose model inference, feature computation, and analytics.
• Develop intuitive front-end interfaces and internal tools using React/Angular/Vue to operationalize model insights and user workflows.
• Implement containerized services with Docker; automate build/test/deploy via CI/CD (Tekton, Harness, Git-based pipelines).
• Use Ansible for configuration management, environment provisioning, and repeatable deployments across Linux/Windows.
• Establish secure-by-design practices (authentication/authorization, secret management, data access controls) and enforce coding standards.
• Instrument applications and pipelines with monitoring and logging; drive performance tuning, memory management, and cost optimization.
• Apply GenAI techniques (prompt engineering, RAG, fine-tuning) and deep learning methods to solve practical user and business problems.
• Build evaluation harnesses and guardrails for LLM quality, safety, hallucination reduction, and bias assessment; iterate based on telemetry.
• Collaborate with product, data, security, and platform teams to prioritize roadmaps and translate ambiguous problems into delivered capabilities.
• Create clear technical documentation, architecture diagrams, and runbooks; participate in design and code reviews.
• Appropriately assess risk when business decisions are made, demonstrating consideration for the firm’s reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.
• Ability to build partnerships with cross-function leaders.

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

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