Full Stack Engineer

About the Company : Well-funded AI sports technology startup delivering real-time, cloud-native platforms to enterprise customers.

About the Role : This role is focused on customer-specific deployments, cloud-native infrastructure, and ultra-low-latency integrations. You will work across backend, frontend, and infrastructure layers and will be responsible for integrating the platform into client environments using reverse-pattern integrations via multi-tenant deployment, WebSockets and RESTful APIs. The role is based in Delhi/NCR and requires travel for on-site deployments and production go-lives.

Responsibilities :

• Develop and customise full-stack components using Node.js and modern frontend frameworks.
• Integrate services into client-owned environments using reverse-pattern integrations via WebSockets and RESTful APIs.
• Design and implement ultra-low-latency data flows, including connection lifecycle handling, back-pressure control, retry logic, and failover strategies.
• Build and maintain backend services backed by PostgreSQL, optimised for high-throughput and low-latency workloads.
• Provision, deploy, and manage Azure infrastructure using Infra-as-Code (mandatory).
• Containerise services using Docker and deploy/manage workloads on Kubernetes (AKS).
• Configure and manage Azure API Management (APIM) for secure, high-volume, low-latency API traffic.
• Participate in on-site customer workshops and go-live support.
• Monitor, debug, and optimise performance of latency-sensitive production systems.

Qualifications :

• Strong production experience with Node.js and PostgreSQL systems.
• Reverse-pattern integration into customer environments using WebSockets and/or RESTful APIs.
• Proven experience building ultra-low-latency, real-time systems.
• Microsoft Azure Infrastructure experience, including:
• AKS (Azure Kubernetes Service)
• Azure API Management (APIM)
• Networking, Key Vault, Storage, Monitoring
• Strong customer management and stakeholder communication skills.
• Ability to lead technical discussions around integration design, latency constraints, and deployment trade-offs.
• Willingness to travel frequently for customer-side deployments and operational support.
• Experience with Sports Media.

Preferred Skills :

• Experience fine-tuning large language models or generative AI for domain-specific applications.
• Experience developing evaluation frameworks for generative AI models.
• Familiarity with Azure cloud services (e.g., Azure Machine Learning, Azure Kubernetes Service, or Azure Data Lake) for model development and deployment.
• Experience with real-time or streaming data for sports applications.
• Knowledge of reinforcement learning or multimodal AI models.
• Familiarity with sports technologies, such as player tracking systems or wearables.
• Contributions to open-source AI/ML projects or published research in relevant fields.