Senior Full-Stack Engineer – Scalable AI Applications

About the Role

We are looking for an experienced Senior Full-Stack Engineer to join our engineering team and take ownership of building and scaling complex features for a live, production-grade AI-powered platform.

This is not a conventional full-stack role focused primarily on standard web development. The platform is already in production and growing, and the engineering challenges involve scalability, real-time processing, AI integration, application performance, reliability, and evolving product architecture.

We are looking for an engineer who enjoys solving problems where the implementation path may not be immediately obvious. You should be comfortable investigating complex technical challenges, evaluating alternative approaches, understanding trade-offs, and taking solutions from architecture through production.

You will work hands-on across React, Python, Django, databases, APIs, caching, asynchronous processing, real-time communication, cloud infrastructure, and AI integrations, while collaborating closely with AI engineers and senior technology leaders.

Key ResponsibilitiesFull-Stack Product Engineering

- Design, develop, and own complex product features across both frontend and backend systems.
- Build scalable, responsive, and maintainable frontend applications using React.
- Design and develop high-performance backend services and APIs using Python and Django.
- Take complete ownership of technical problems from investigation and architecture through development, testing, deployment, monitoring, and production troubleshooting.
- Build reusable and maintainable components that support continuous product evolution.

Scalability & Performance Engineering
- Design applications capable of scaling to 100,000+ registered users, 10,000+ daily active users, and 100+ concurrent users.
- Build and optimize systems supporting real-time user interactions and high levels of concurrent application traffic.
- Identify and resolve performance bottlenecks across frontend applications, backend services, APIs, databases, AI services, and infrastructure.
- Apply appropriate scalability patterns including:
- Caching
- Asynchronous processing
- Background jobs
- Message queues
- Database optimization
- Load balancing
- Horizontal scaling
- WebSockets and real-time communication
- API optimization
- Rate limiting
- Conduct performance analysis and help improve application response times, throughput, and resource utilization.

AI & LLM Integration
- Collaborate closely with AI engineers to integrate LLMs, AI APIs, machine-learning services, and AI models into production applications.
- Build application workflows around RAG pipelines, vector search, AI-powered search, streaming LLM responses, and real-time AI interactions.
- Design robust application interfaces between AI services and the core product.
- Handle challenges such as AI service latency, streaming responses, failures, retries, timeouts, and concurrent AI requests.
- Help translate AI capabilities into scalable, reliable, user-facing product features.

Architecture & Engineering
- Participate actively in application and platform architecture discussions.
- Work with senior engineering and technology leaders to design architecture for new product capabilities.
- Evaluate different implementation approaches based on scalability, performance, reliability, security, maintainability, and development effort.




- Break down complex technical requirements into clear and practical implementation approaches.
- Continuously improve existing architecture as product usage and technical requirements evolve.
- Identify technical debt and recommend practical approaches for addressing it.

Production Reliability & Troubleshooting
- Diagnose complex production issues and identify root causes rather than relying on temporary fixes.
- Improve the reliability, maintainability, observability, and performance of production systems.
- Implement appropriate logging, monitoring, error handling, alerting, and application health mechanisms.
- Proactively identify scalability and reliability risks before they become production issues.
- Support production deployments and troubleshoot issues across application and infrastructure layers.

Engineering Leadership & Mentorship
- Maintain high standards for code quality, testing, documentation, and engineering practices.
- Conduct code reviews and review technical approaches proposed by other engineers.
- Provide technical guidance and mentorship to junior engineers.
- Help team members improve their engineering quality, architecture thinking, debugging, and problem-solving capabilities.
- Share technical knowledge, engineering practices, and lessons learned across the team.
- Contribute to building a strong engineering culture focused on ownership, quality, experimentation, and continuous improvement.

What We Are Looking ForCore Technical Skills
- 5+ years of professional software engineering experience, preferably building and operating production applications.
- Strong hands-on experience with React and modern frontend development.
- Strong backend development experience with Python and Django.
- Strong understanding of REST APIs, application architecture, authentication, databases, and backend system design.
- Experience designing, building, or operating applications supporting significant user traffic and concurrency.
- Strong understanding of relational databases and practical experience with database design, indexing, query optimization, and performance tuning.
- Experience working with caching, asynchronous processing, background jobs, and queues.
- Understanding of WebSockets, Server-Sent Events, or similar real-time communication approaches.
- Experience diagnosing production performance, scalability, and reliability issues.
- Good understanding of cloud-native application architecture and deployment practices.

Problem-Solving & Ownership We are particularly interested in engineers who are motivated by difficult technical problems.

You should be someone who can:

- Independently investigate unfamiliar technical problems.
- Understand the root cause before deciding on a solution.
- Research and evaluate alternative technical approaches.
- Work effectively when requirements or implementation paths are ambiguous.
- Make informed engineering trade-offs between speed, scalability, maintainability, and quality.
- Challenge existing approaches constructively when a better solution is available.
- Take ownership rather than waiting for detailed technical instructions.




- Stay persistent when the first implementation approach does not work.
- Think beyond the immediate feature and consider its long-term impact on the platform.

Technology Landscape You should have solid experience with several of the following technologies or equivalent platforms:

Frontend:

React, JavaScript/TypeScript, modern frontend frameworks and libraries

Backend:

Python, Django, Django REST Framework, REST APIs

Data & Caching:

PostgreSQL/MySQL, Redis, database indexing and optimization

Async & Real-Time:

Celery, message queues, background workers, WebSockets, Server-Sent Events

AI:

LLM APIs, AI/ML services, RAG, vector databases, embeddings, streaming AI responses

Cloud:

AWS, EC2, RDS, S3, CloudFront, Load Balancers, Lambda, Redis/ElastiCache or equivalent services

DevOps & Operations:

Docker, CI/CD, application monitoring, centralized logging, observability, performance monitoring

Nice to Have

- Experience building high-concurrency or real-time applications.
- Experience architecting applications on AWS or another major cloud platform.
- Experience with Redis, Celery, Kafka, RabbitMQ, SQS, or similar messaging technologies.
- Experience integrating LLMs or AI APIs into production applications.
- Experience implementing RAG and AI-powered search solutions.
- Experience with vector databases or semantic search technologies.
- Experience building applications with streaming AI responses.
- Experience with Docker and containerized production environments.
- Experience implementing CI/CD pipelines and automated deployment practices.
- Experience with monitoring, logging, tracing, and production observability.
- Experience conducting application performance testing and optimization.
- Experience working in a startup, product company, or rapidly scaling technology environment.

Mindset We Value

We value engineers who

- Enjoy difficult problems rather than avoiding them.
- Take end-to-end ownership of what they build.
- Are comfortable operating with ambiguity.
- Investigate problems deeply instead of applying temporary fixes.
- Learn unfamiliar technologies when required.
- Think about scalability before scalability becomes a problem.
- Consider production reliability as part of development.
- Proactively identify technical risks.
- Communicate technical trade-offs clearly.
- Challenge assumptions when better approaches are possible.
- Balance engineering excellence with the execution speed required in a growing organization.
- Help other engineers become better problem solvers.

Why Join This Role This is an opportunity to work on a live, rapidly evolving AI platform where engineering decisions directly influence product performance, scalability, reliability, and user experience.

You will not simply receive predefined development tasks. You will be expected to understand the underlying problem, participate in solution architecture, evaluate technical approaches, build the solution, and take ownership of its performance in production.

You will work at the intersection of full-stack engineering, scalable application architecture, cloud infrastructure, real-time systems, and Generative AI.

If you enjoy building sophisticated applications, solving problems without obvious answers, and taking meaningful ownership of how a technology platform evolves, this role provides the opportunity to do exactly that.

Pay: ₹700,000.00 - ₹1,200,000.00 per year

Experience

- Total: 4 years (Required)

Work Location: In person

📌 Full Stack Developer (Bengaluru)
🏢 Promptora AI
📍 Bengaluru