Backend Engineer Generative AI (Infra)

Role & resp

Backend Engineer Generative AI (Infra)

Experience Required: 2 5 Years

Location: Bangalore (In-office)Brookfeild

Employment Type: Full-Time

About the Role

Backend Engineer with experience in AI-based systems

banking or enterprise-grade applications

Key Responsibilities

• Backend Architecture & Development

Design and develop robust backend services to support AI and Generative AI workloads.

RESTful and GraphQL APIs

Implement modular backend components for scalable, high-performance AI operations.

• Generative AI Pipeline Integration

Generative AI models

Vector Databases

TensorFlow Serving, TorchServe, FastAPI, or custom endpoints

• API Management & Optimization

Develop and manage secure APIs for AI-driven services, ensuring version control, authentication (OAuth2, JWT), and scalability.

Integrate third-party AI APIs (OpenAI, Anthropic, Google Gemini, Stability AI, etc.) within internal systems.

Monitor API usage, optimize latency, and handle concurrency for high-throughput AI operations.

• System & Environment Setup

Configure backend environments using Docker, Kubernetes, and CI/CD pipelines for automated deployments.

AWS, Azure, or GCP

Set up development environments and backend utilities for cross-functional AI and data teams.

• Performance & Security

Optimize server performance for inference-heavy AI pipelines through caching, queuing, and load balancing.

Ensure compliance with data privacy and security regulations, especially in financial and regulated domains.

Implement observability tools for monitoring, tracing, and performance analytics.

• Collaboration

Work closely with AI/ML engineers, data scientists, frontend developers, and DevOps teams.

Contribute to architecture discussions, documentation, and backend process improvements.

Participate in agile ceremonies, code reviews, and team-level technical design sessions.

Required Technical Skills

• Languages:

  Python (primary), Node.js and Java

• Backend Frameworks:

  FastAPI, Flask, Django, Express.js, Spring Boot

• AI & Generative Tools:

LLMs (GPT, Claude, Gemini, LLaMA, Mistral)

transformer models

prompt engineering concepts

• Databases:

  PostgreSQL, MongoDB, Redis, Elasticsearch

• Vector Databases:

  Pinecone, Weaviate, Milvus, FAISS (for RAG systems)

• Infrastructure & DevOps:

  Docker, Kubernetes, Jenkins, GitLab CI/CD, AWS Lambda, ECS, or GCP Cloud Run

• Monitoring:

  Prometheus, Grafana, ELK Stack, New Relic

• API Technologies:

  REST, GraphQL, gRPC

Preferred Qualifications

• Experience with

  AI product backend systems

  or

  enterprise/banking-grade software applications

  .
• Exposure to

  AI pipeline orchestration

  tools (LangChain, LlamaIndex, or Haystack).
• Understanding of

  model lifecycle management

  ,

  vector embeddings

  , and

  inference scaling

  .
• Familiarity with

  data encryption, tokenization, and compliance frameworks

  (PCI DSS, ISO 27001, etc.).

Soft Skills

• Strong problem-solving and debugging skills.
  
• Excellent communication and collaboration with cross-functional teams.
  
• High attention to detail and performance optimization.
  
• Curiosity and enthusiasm for emerging AI technologies and architectures.
  

Education

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Artificial Intelligence, or a related discipline.
  
• Certifications in

  AI/ML

  ,

  Cloud Architecture

  , or

  Backend Development

  are a plus.

Why Join Us

• Work at the intersection of

  backend engineering and Generative AI innovation

  .
• Build production-ready systems for intelligent, large-scale applications.
  
• Collaborate with a team pushing the boundaries of applied AI and infrastructure optimization.

  onsibilities

Preferred candidate profile