Senior AI Engineer

AuthBridge; Gurugram District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

AuthBridge in Gurugram seeks a Senior AI Engineer to design and build scalable backend systems using FastAPI, Celery, and modern Python, with a focus on Generative AI and Agentic AI. You will implement robust data validation with Pydantic, develop RESTful APIs, and integrate LLMs and prompt-engineered solutions into production workflows, collaborating with data scientists and DevOps.

You will also own end-to-end AI automation projects, ensure observability, performance, and reliable deployment

Qualifications

• 4-6 years of hands-on Python development experience building scalable backend systems.
• Proven experience designing production-grade RESTful APIs with FastAPI.
• Deep understanding of Python's async programming and Pydantic data modeling.
• Experience with LLMs, Generative AI, and Prompt Engineering.
• Strong knowledge of SQLAlchemy and relational databases.
• Experience with Docker and container orchestration.
• Familiarity with observability tools (Prometheus, Grafana, AWS CloudWatch).

Responsibilities

• Design, build, and maintain high-performance RESTful APIs with FastAPI and async patterns.
• Implement data validation and settings management with Pydantic.
• Integrate SQLAlchemy-based async data storage and retrieval.
• Develop and deploy background tasks with Celery using RabbitMQ/Redis.
• Build front-end interfaces with React/Next.js to complement AI services.
• Ensure observability with logging, metrics, and tracing; optimize performance.
• Collaborate with data scientists, DevOps, and product stakeholders.

Skills

Python

Async programming

API design

Prompt engineering

Observability

Education

Bachelor's or Master's in CS/AI

Tools

FastAPI

Celery

RabbitMQ

Redis

Job description

We are seeking a talented and versatile Senior AI Engineer with a strong foundation in

Generative AI, Agentic AI, and Software Development and building robust, high-performance

systems to join our growing team in Gurugram. This role requires practical experience in

building and deploying scalable, reliable, and observable applications using FastAPI, Celery,

and modern Python.

Key Responsibilities

API & Solution Development

• Design, build, and maintain high-performance, scalable RESTful APIs using FastAPI,
• leveraging its async programming patterns for maximum concurrency.
• Implement rigorous data validation and settings management using Pydantic.
• Write clean, efficient, testable, and well-documented Python code.
• Integrate database solutions using SQLAlchemy for efficient, asynchronous data storage and retrieval.
• Design and implement fault-tolerant background tasks and distributed task queues using Celery (with RabbitMQ/Redis as brokers) to handle long-running processes and offload work from the API.
• Containerize applications using Docker to ensure seamless deployment and

Prompt Engineering & GenAI Integration

• Design, develop, test, and refine complex prompts for Large Language Models (LLMs) and other Generative AI models.
• Optimize prompts to ensure accuracy, safety, and desired contextual output.
• Integrate prompt-engineered solutions and Generative AI model outputs into the core application logic via FastAPI endpoints.
• Evaluate cost-performance trade-offs across a broad range of proprietary and open-source LLMs to select the right model for a given use case.

Agentic AI

• Design, develop, test, and refine complex agentic flows using agentic AI frameworks like
• Architect Agentic AI applications using MCP, RAG, GraphRAG, ReAct approaches.

Full-Stack & AI-Assisted Development

• Build lightweight front-end interfaces (React, Next.js) to complement backend AI services, leveraging vibe-coding tools such as Claude Code or Codex.
• Build and deploy full-stack applications end-to-end using the above stack (FastAPI/Celery backend + React/Next.js frontend).
• Own AI automation projects end-to-end — from architecture and prompt/agent design through backend integration, frontend delivery, and production deployment.

Performance, Reliability & Deployment

• Design and execute performance benchmarks and load testing using tools like Locust to ensure scalability and identify bottlenecks under pressure.
• Implement robust observability practices, including structured logging, metrics (e.g., Prometheus), and tracing to monitor system health and performance.
• Deploy containerized applications into production, focusing on high reliability, fault tolerance, and scalability.
• Optimize database queries and application logic for speed and low latency.
• Stay abreast of advancements in Generative AI, prompt engineering, and
• Experiment with new tools, frameworks, and methodologies to drive innovation within the team.
• Work closely with cross-functional teams including data scientists, backend engineers, DevOps, and product stakeholders.
• Present technical insights clearly and contribute to peer reviews and team knowledge sharing.

Qualification & Functional Skills

General

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
• 4-6 years of hands-on experience in Python development, with a strong focus on building scalable backend systems.
• Proven, hands-on experience designing and building production-grade RESTful APIs using FastAPI.
• Deep understanding of Python's async programming patterns (async/await) and their practical application.
• Expert-level understanding of Pydantic for data modeling and validation.
• Demonstrable experience in Prompt Engineering for Generative AI models.
• Strong proficiency with SQLAlchemy (preferably with its async capabilities) and relational databases.
• Experience with containerization and orchestration using Docker.
• Hands-on experience with performance and load testing frameworks, specifically Locust.
• Familiarity with observability tools and practices (e.g., AWS Cloudwatch, Prometheus, Grafana, ELK stack) to ensure system reliability.
• Experience with version control systems (e.g., Git).
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration abilities.

Mandatory

• Backend & Distributed Systems: Celery, FastAPI, RabbitMQ, Redis.
• Vibe-Coding Tool Familiarity: Claude Code or Codex.
• Frontend (familiarity to build with vibe-coding tools): React, Next.js.
• Experience with cost-performance trade-offs across a broad range of LLMs, including open-source LLMs.
• Built and deployed full-stack applications using tools from the above stack.
• Handled AI automation projects end-to-end using the above tools.

Nice to Have

• Backend & Distributed Systems: Celery, FastAPI, RabbitMQ, Redis, Temporal.
• Frontend (familiarity to build with vibe-coding tools): React, Next.js, CopilotKit, Vercel AI SDK.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services.

Role: Software Development - Other

Industry Type: IT Services & Consulting

Department: Engineering - Software & QA

Role Category: Software Development

Education: UG: B.Tech/B.E. in Computers or a related field