Backend Engineer Generative AI

Role & resp

Backend Engineer Generative AI (Infra)

Experience Required: 2 5 Years

Location: Bangalore (In-office)Brookfeild

Employment Type: Full-Time

About the Role

We are looking for a Backend Engineer with experience in AI-based systems, particularly in building and maintaining Generative AI pipelines and scalable backend infrastructures. The ideal candidate will have a solid background in backend engineering, API design, and AI model integration, with a working understanding of LLMs, diffusion models, and multimodal AI applications.

You will be responsible for developing and managing backend systems that power AI services — from model APIs to data retrieval pipelines — ensuring they run efficiently and securely in production. Experience in banking or enterprise-grade applications is highly preferred, as the role requires a strong understanding of security, performance, and compliance standards.

Key Responsibilities

• Backend Architecture & Development

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

Build and optimize RESTful and GraphQL APIs for model inference, prompt processing, and data access.

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

• Generative AI Pipeline Integration

Collaborate with AI engineers to integrate and deploy Generative AI models (LLMs, diffusion models, text-to-image, speech-to-text, etc.) into production environments.

Implement retrieval-augmented generation (RAG) pipelines using Vector Databases like Pinecone, Weaviate, FAISS, or Milvus.

Handle AI model serving and inference optimization using frameworks like 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.

Manage scalable cloud environments on AWS, Azure, or GCP, ensuring load balancing and fault tolerance.

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), and Java
• Backend Frameworks: FastAPI, Flask, Django, , Spring Boot
• AI & Generative Tools:

Familiarity with LLMs (GPT, Claude, Gemini, LLaMA, Mistral) and diffusion models (Stable Diffusion, Midjourney APIs)

Experience integrating transformer models via Hugging Face or OpenAI APIs

Understanding of prompt engineering concepts and model-serving best practices

• 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