- Location
- Bengaluru
- Workplace
- Remote, Hybrid
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Closing date
- Today
- Source
- CareersPage
Description
We are seeking a highly skilled Senior AI Backend Engineer to design, develop, and scale backend systems that power AI-driven products. This role sits at the intersection of backend engineering, machine learning systems, and production infrastructure, ensuring AI solutions are scalable, secure, reliable, and production-ready.
The ideal candidate must have strong experience in Python, TensorFlow, and Keras, along with expertise in deploying and managing AI/ML solutions in production environments.
Location: Bengaluru, Hyderabad (Hybrid)
Shift Timings: 2:00 PM – 11:00 PM IST
Work Schedule: Monday to Friday
Notice Period: Immediate Joiners only
Key Responsibilities
Design and develop scalable backend services supporting AI-powered applications.
Build and maintain APIs for model inference, including LLMs, NLP, computer vision, and recommendation systems.
Deploy, manage, and optimize machine learning models in production environments.
Develop data pipelines for model training, evaluation, and real-time inference.
Optimize system performance to support low-latency, high-throughput AI workloads.
Implement monitoring, logging, and observability solutions for AI services.
Ensure system security, reliability, scalability, and operational excellence.
Collaborate with Machine Learning Engineers to productionize AI and ML models.
Work closely with DevOps teams to manage cloud infrastructure and CI/CD pipelines.
Required Qualifications
7–8 years of backend development experience.
Strong proficiency in Python (preferred).
Must have hands-on experience with TensorFlow and Keras.
Experience developing RESTful APIs and/or GraphQL services.
Experience working with machine learning frameworks such as TensorFlow or PyTorch.
Proven experience deploying machine learning models into production environments.
Hands-on experience with Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and Agentic AI systems.
Experience with cloud platforms such as AWS, GCP, or Azure.
Strong understanding of SQL and NoSQL databases.
Experience with Docker and containerization technologies.
Good understanding of distributed systems and microservices architecture.
Preferred Qualifications
Experience with model serving frameworks such as FastAPI, Triton Inference Server, or TorchServe.
Knowledge of vector databases such as Pinecone, Weaviate, or FAISS.
Experience with event streaming platforms such as Kafka or Google Pub/Sub.
Familiarity with Kubernetes and container orchestration.
Understanding of MLOps practices, frameworks, and tooling.
Experience working in high-growth or startup environments.
Technical Skills
Backend: Python, FastAPI, REST APIs, GraphQL, Microservices
AI/ML: TensorFlow, Keras, PyTorch, LLMs, RAG, Agentic AI
Cloud: AWS, Azure, GCP
Databases: SQL, NoSQL, Vector Databases
DevOps & Infrastructure: Docker, Kubernetes, CI/CD
Messaging & Streaming: Kafka, Pub/Sub
Ideal Candidate
The ideal candidate combines strong backend engineering fundamentals with hands-on experience building and deploying AI-powered applications. They should be comfortable working across backend services, cloud infrastructure, machine learning systems, and production AI environments.
