Full Stack Engineer

Talent Toppers

0 years

0 Lacs

gurugram haryana india

Posted:5 days ago| Platform:

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Skills Required

stack ai technology latency layers deployment websockets node.js design data logic failover postgresql azure code docker kubernetes api management integration networking vault storage communication constraints tuning evaluation learning service model development reinforcement tracking ml research

Work Mode

On-site

Job Type

Full Time

Job Description

About the Company

About the Role

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.

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