Role

As a Senior Backend Developer at Nasiko, you will design, build, and optimize high-performance backend systems that power our distributed AI ecosystem. You will collaborate closely with ML engineers, platform teams, and infrastructure groups to deploy AI-powered services, scale intelligent workflows, and serve models efficiently across diverse environments. Your work will be central to Nasiko’s mission of enabling robust, interoperable, and adaptive AI coordination..

Core Responsibilities

• Develop and maintain backend systems, microservices, and APIs using Golang.

• Architect and deploy distributed infrastructure for high-throughput AI workloads.

• Collaborate with ML engineers to integrate trained models into scalable production environments.

• Build and maintain real-time and batch inference pipelines for AI-driven tasks.

• Contribute to DevOps and MLOps workflows, including CI/CD automation, observability, monitoring, and autoscaling.

• Ensure high availability, performance, and security across backend deployments.

• Optimize internal tooling, model-serving infrastructure, and large-scale system performance.

Skills and Qualifications

Required:

• Strong professional experience with Golang in production-grade systems.

• Deep understanding of distributed systems, concurrency models, and network programming.

• Familiarity with ML frameworks such as PyTorch, TensorFlow, or JAX.

• Hands-on experience with model-serving platforms like Triton Inference Server, TorchServe, ONNX Runtime, or Ray Serve.

• Proficiency in containerization (Docker) and orchestration (Kubernetes).

• Experience with MLOps tools such as MLflow, Weights & Biases, Kubeflow, or Airflow.

• Strong grasp of cloud platforms (AWS, GCP, Azure) and infrastructure-as-code.

• Experience with SQL/NoSQL databases, caching systems (Redis), and message queues (Kafka, RabbitMQ).

• Proficiency in Git and modern GitHub/GitLab workflows.

• Bachelor’s degree in Computer Science, Engineering, or related fields is a plus.

Nice to Have:

• Experience working with LLMs or foundation model architectures.

• Familiarity with vector databases such as FAISS, Pinecone, or Weaviate.

• Exposure to LLM orchestration frameworks (LangChain, LlamaIndex, Haystack).

• Experience with graph processing, streaming systems, or real-time inference platforms.

• Interest in AI evaluation, interpretability, or safety methodologies.

Why Join Us?

• Build state-of-the-art infrastructure powering applied AI at scale.

• Collaborate with a world-class team of engineers, scientists, and researchers.

• Contribute to open-source tooling and research-driven development.

• Competitive compensation with a dynamic, in-office culture in Bangalore.