Python Developer - Backend

Omnissa; Bengaluru; On-site; INR 1,500,000 - 3,000,000; Full time

Job summary

Omnissa is looking for an AI Application Software Engineer to design and develop AI-driven application features within the cloud-scale environment. The role requires collaboration with platform, product, and engineering teams to integrate intelligent capabilities into applications, fostering a culture of engineering excellence.

The ideal candidate should have 5 to 16 years of software engineering experience and proficiency in Python and another programming language, with a strong foundation in scalable applications and AI/ML integration.

Qualifications

• 5 to 16 years of experience as a Software Engineer role in building scalable applications.
• Strong proficiency in Python and at least one additional programming language (Java, Go, or C++).
• Experience developing backend systems, APIs, and microservices architectures.
• Experience integrating AI/ML capabilities into applications.

Responsibilities

• Design, develop, and deliver AI-powered application features and services.
• Build scalable and reliable distributed systems, ensuring performance and high availability.
• Collaborate with AI/ML engineers to integrate models into production-grade applications.

Skills

Python

Java

Go

C++

REST APIs

gRPC

Tools

Containerization technologies

Orchestration frameworks

Observability tools

Job description

Our platform manages millions of devices across multiple operating systems, requiring exceptional performance, scalability, availability, and resilience. You will join the AI Platform Team, responsible for building and enabling AI-driven application experiences across the Omnissa product ecosystem.

As an AI Application Software Engineer, you will design, develop, and integrate intelligent application features powered by AI/ML technologies, including LLMs and data-driven components. You will work closely with platform, product, and engineering teams to deliver seamless AI-powered capabilities within a cloud-scale environment while adhering to strong software engineering practices.

You will own engineering initiatives end-to-end and help foster a culture of high ownership, continuous improvement, and engineering excellence.

Responsibilities

• Design, develop, and deliver AI-powered application features and services.
• Build and integrate AI capabilities such as LLM-based features, automation workflows, and intelligent user experiences into applications.
• Develop backend services, APIs, and application logic that interact with AI/ML systems and models.
• Collaborate with AI/ML engineers to integrate models into production-grade applications.
• Build scalable and reliable distributed systems, ensuring performance and high availability.
• Implement observability, monitoring, and logging for AI-driven application components.
• Participate in system design, architecture discussions, and code reviews.
• Continuously improve system performance, reliability, and developer productivity.
• Stay current with advancements in AI technologies (e.g., LLMs, embeddings, agent frameworks) and apply them to product use cases.

What will you bring to Omnissa?

Required Skills & Experience

• 5 to 16 years of experience as a Software Engineer role in building scalable applications.
• Strong proficiency in Python and at least one additional programming language (Java, Go, or C++).
• Experience developing backend systems, APIs, and microservices architectures.
• Experience building scalable services using REST/gRPC APIs.
• Experience integrating AI/ML capabilities into applications (e.g., APIs for LLMs or ML services).
• Strong understanding of data structures, algorithms, and system design principles.
• Experience with containerization and orchestration technologies
• Strong problem-solving skills and ability to collaborate effectively in Agile environments.
• Highly motivated, adaptable, and eager to learn new technologies.

Preferred Skills

• Experience building applications using LLMs, RAG systems, or AI agents.
• Familiarity with vector databases and embedding models.
• Experience with orchestration frameworks (e.g., LangChain, LangGraph).
• Knowledge of real-time data processing and event-driven architectures.
• Exposure to observability tools and monitoring systems for AI applications.