Job description

About Us Deccan AI is AI training, evaluations and Enterprise AI solutions startup headquartered in the Bay Area. We are founded by IIT Bombay, IIM Ahmedabad and ex-Google alumni, and work with some of the top AI frontier labs in the world. Backed by Prosus Ventures and A91 we are expanding the team in US, San Mateo. About the Role We’re looking for a Backend Engineer to design, build, and scale the backend systems that power Deccan AI’s data, AI operations, and internal platforms. You’ll work on distributed systems, APIs, data-intensive applications, workflow automation, and services that support large-scale AI data and evaluation programs. This role involves solving complex engineering problems around scale, reliability, performance, and operational efficiency . You’ll work closely with Product, ML, Data, and Operations teams to turn complex business and AI workflows into robust, scalable software systems. What You’ll Do • Design, develop, and maintain scalable backend services, APIs, and microservices . • Build systems that support large-scale AI data generation, annotation, evaluation, and operational workflows . • Design efficient data models, database schemas, and backend architectures for high-volume applications. • Build workflow orchestration and automation systems that improve operational efficiency and reduce manual processes. • Develop reliable APIs and services used by internal platforms, AI/ML systems, and enterprise applications. • Work with asynchronous processing, queues, event-driven systems, and distributed architectures where required. • Optimize backend systems for performance, scalability, reliability, and cost . • Integrate internal systems with third-party APIs, enterprise platforms, and external services. • Build monitoring, logging, alerting, and observability into production systems. • Collaborate with ML Engineers and Data Scientists to productionize models and integrate ML capabilities into backend applications. • Work closely with Product, Operations, and Engineering teams to understand requirements and deliver end-to-end solutions. • Participate in architecture discussions, code reviews, testing, debugging, and production support. • Take ownership of systems from design → development → deployment → monitoring → continuous improvement . What You’ll Bring • 3–7 years of experience in backend software engineering or a related role. • Strong proficiency in Python, Java, Go, or similar backend programming languages . • Strong understanding of data structures, algorithms, object-oriented design, and software engineering fundamentals . • Hands-on experience building and scaling REST APIs, backend services, and distributed systems . • Strong experience with relational databases such as PostgreSQL / MySQL and understanding of database design and optimization. • Experience with caching, queues, asynchronous processing, and distributed systems. • Experience with cloud platforms such as AWS, GCP, or Azure . • Strong understanding of system design, scalability, reliability, and performance optimization. • Experience with Git, CI/CD, testing, debugging, and production engineering practices. • Strong ownership and ability to independently drive projects from problem definition through production. Preferred Qualifications • Experience working in AI/ML, SaaS, data platforms, or high-growth technology companies . • Experience building systems handling large datasets, high-volume workflows, or distributed workloads . • Experience with technologies such as Redis, Kafka, RabbitMQ, Celery, Kubernetes, Docker, or similar systems . • Experience with workflow orchestration or job-processing systems. • Familiarity with ML infrastructure, model-serving systems, or AI application architectures. • Experience building internal platforms or operational tooling used by multiple teams. • Strong understanding of observability and production monitoring. • Experience working in a fast-paced startup environment where requirements evolve rapidly.

Requirements

Must-haves

We’re looking for a Backend Engineer to design, build, and scale the backend systems that power Deccan AI’s data, AI operations, and internal platforms.
You’ll work closely with Product, ML, Data, and Operations teams to turn complex business and AI workflows into robust, scalable software systems.
What You’ll Do
Design, develop, and maintain scalable backend services, APIs, and microservices .
Build systems that support large-scale AI data generation, annotation, evaluation, and operational workflows .
Design efficient data models, database schemas, and backend architectures for high-volume applications.
Build workflow orchestration and automation systems that improve operational efficiency and reduce manual processes.
Develop reliable APIs and services used by internal platforms, AI/ML systems, and enterprise applications.
Work with asynchronous processing, queues, event-driven systems, and distributed architectures where required.
Optimize backend systems for performance, scalability, reliability, and cost .
Integrate internal systems with third-party APIs, enterprise platforms, and external services.
Build monitoring, logging, alerting, and observability into production systems.
Collaborate with ML Engineers and Data Scientists to productionize models and integrate ML capabilities into backend applications.
Work closely with Product, Operations, and Engineering teams to understand requirements and deliver end-to-end solutions.
Participate in architecture discussions, code reviews, testing, debugging, and production support.
Take ownership of systems from design → development → deployment → monitoring → continuous improvement .

Nice-to-haves

Experience working in AI/ML, SaaS, data platforms, or high-growth technology companies .
Experience building systems handling large datasets, high-volume workflows, or distributed workloads .
Experience with technologies such as Redis, Kafka, RabbitMQ, Celery, Kubernetes, Docker, or similar systems .
Experience with workflow orchestration or job-processing systems.
Familiarity with ML infrastructure, model-serving systems, or AI application architectures.
Experience building internal platforms or operational tooling used by multiple teams.
Strong understanding of observability and production monitoring.
Experience working in a fast-paced startup environment where requirements evolve rapidly.

Application prep

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Keywords to mirror

aimlpythonjavagorestawsgcpazureci/cdkubernetesdocker

Platform: dover
Effort: medium