Job Description
This role is for one of the Weekday's clients
Salary range: Rs 2500000 - Rs 3500000 (ie INR 25-35 LPA)
Min Experience: 4 years
Location: Bengaluru
JobType: full-time
This role is ideal for a backend engineer who enjoys building AI-first platforms from the ground up. You will work on scalable backend systems that power advanced AI-driven developer tools, collaborating closely with AI/ML researchers and product teams to turn cutting-edge research into reliable, enterprise-ready solutions. The position offers hands-on ownership across system design, AI inferencing, and production deployments, with a strong focus on performance, security, and real-world usability.
Requirements
Key Responsibilities
- Design, develop, and maintain scalable, robust backend systems that support AI-powered products and developer tools
- Architect and implement advanced Retrieval Augmented Generation (RAG) pipelines and knowledge graph–based systems for domain-specific language models
- Build and optimize self-hosted AI inferencing pipelines, ensuring high performance for on-premise, edge, and enterprise deployments
- Collaborate with AI/ML researchers to translate models, experiments, and prototypes into production-grade backend services
- Design and implement APIs and data pipelines that enable complex AI workflows, integrations, and enterprise use cases
- Support deployment of AI solutions across cloud and on-premise environments, including GPU and accelerator-based setups
- Work closely with founders, product managers, and engineers to convert AI capabilities into meaningful product features
- Write clean, maintainable, and well-tested code while actively participating in design discussions and code reviews
- Continuously optimize system performance, reliability, security, and data integrity for enterprise AI platforms
What Makes You a Great Fit
- A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, with 4–5 years of backend engineering experience focused on AI/ML systems
- Strong proficiency in Python and backend frameworks such as FastAPI, Django, or Flask
- Hands-on experience designing and implementing RAG systems, including embeddings, vector databases, and retrieval strategies
- Familiarity with knowledge graph technologies such as Neo4j or FAISS and their application in AI systems
- Experience with self-hosted AI inferencing, including optimization techniques like quantization and pruning
- Practical exposure to deploying AI workloads on GPUs or specialized AI accelerators
- Solid understanding of system design, data structures, algorithms, and distributed backend architectures
- An ownership-driven mindset with strong problem-solving skills and the ability to work effectively in a fast-moving environment
- Bonus points for experience with enterprise on-premise deployments, AI security and compliance practices, MLOps, LLM fine-tuning, or startup environments
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