Job Overview

Persistent is hiring an AI Native Engineer in Pune for a full-time opportunity focused on building enterprise-grade artificial intelligence applications. The role is designed for an experienced software engineer who can combine strong programming fundamentals with modern Generative AI, Large Language Models, agentic workflows, cloud platforms, and automation technologies.

In this position, you will help create AI-powered applications, copilots, intelligent agents, and automation solutions that connect with enterprise systems and business workflows. The work involves practical implementation of LLM-based solutions rather than experimentation alone, with an emphasis on reliability, security, observability, governance, and responsible AI. You will work with engineering and business stakeholders to identify valuable AI use cases and turn them into scalable solutions.

Key Responsibilities

• Design and develop AI-powered applications, enterprise copilots, and intelligent agents that address practical business requirements.
• Build Retrieval-Augmented Generation pipelines, vector search workflows, and prompt engineering solutions for production use cases.
• Integrate Large Language Models with enterprise applications, APIs, services, and business workflows.
• Develop AI orchestration solutions capable of coordinating multiple AI components and agents.
• Apply appropriate security, governance, monitoring, observability, and responsible AI practices throughout the solution lifecycle.
• Work closely with business stakeholders, software engineers, and other technical teams to identify suitable AI opportunities and deliver working solutions.
• Contribute reusable AI frameworks, accelerators, implementation patterns, and engineering best practices.
• Develop cloud-native AI solutions using major public cloud platforms and modern application architectures.
• Participate in building scalable services using APIs, microservices, and automated CI/CD processes.
• Explore and apply modern AI-assisted development tools to improve engineering productivity and solution quality.

Required Skills

Candidates should have strong software engineering experience with Java and Python and practical experience developing AI-enabled enterprise applications. Hands-on knowledge of TypeScript and Angular is also expected for this position.

The role requires experience working with LLM platforms such as OpenAI, Claude, Gemini, Azure OpenAI, or comparable services. Applicants should understand how to select, integrate, and use language models within applications while considering reliability, security, and business requirements.

Strong knowledge of RAG, embeddings, vector databases, prompt engineering, and AI agents is important. Experience with AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or equivalent technologies is also relevant.

Candidates should understand cloud application development and have experience with at least one major cloud platform, including Azure, AWS, or GCP. Knowledge of APIs, microservices, and CI/CD is required to support production-ready enterprise solutions.

Preferred Skills

Experience with multi-agent orchestration and advanced Agentic AI architectures is preferred. Familiarity with MCP, or Model Context Protocol, is an additional advantage for engineers working on connected AI agents and tool-based workflows.

Exposure to AI observability, LLMOps, and MLOps can further strengthen an application. Experience using AI-assisted engineering tools such as GitHub Copilot, Claude Code, Cursor, or similar solutions is also valuable.

Candidates who have worked on reusable AI platforms, enterprise automation, production GenAI systems, or complex cloud-native solutions may be particularly well suited to the role.

Education

A Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field is required. AI and Cloud certifications are preferred and can demonstrate additional expertise in the technologies relevant to this position.

Experience

The position requires 5 to 10 years of professional experience, with relevant experience in AI engineering, software development, cloud technologies, or enterprise application engineering. The ideal candidate should have demonstrated experience delivering enterprise-grade Generative AI solutions and should be comfortable taking an AI solution from design through implementation and integration.

Required Technologies

• Java
• Python
• TypeScript
• Angular
• OpenAI
• Claude
• Gemini
• Azure OpenAI
• Large Language Models (LLMs)
• Generative AI
• Agentic AI
• AI Agents
• RAG
• Embeddings
• Vector Databases
• Prompt Engineering
• LangChain
• LangGraph
• Semantic Kernel
• CrewAI
• AutoGen
• MCP (Model Context Protocol)
• Azure
• AWS
• GCP
• APIs
• Microservices
• CI/CD
• AI Observability
• LLMOps
• MLOps
• GitHub Copilot
• Claude Code
• Cursor

Soft Skills

The role requires an AI-first mindset combined with practical software engineering judgment. Candidates should be able to understand business problems, communicate technical possibilities clearly, and work collaboratively with business and engineering teams.

Problem-solving, adaptability, curiosity, and continuous learning are important because AI technologies and development patterns evolve quickly. Strong collaboration skills will help the successful candidate contribute to reusable frameworks and work effectively with teams across different technical areas.

Benefits of Working in this Role

The position offers an opportunity to work with modern AI, cloud, and automation technologies while developing enterprise-grade Generative AI solutions. Persistent states that it provides a talent-development culture with quarterly growth opportunities and company-sponsored higher education and certifications.

The listed benefits also include competitive salary and benefits, employee engagement initiatives, flexible work hours, project-related activities, Long Service awards, annual health check-ups, and insurance coverage including group term life, personal accident, and Mediclaim hospitalization for the employee and specified family members.

Work Mode

The provided job description does not explicitly specify onsite, hybrid, or remote work mode. The position is based in Pune.

Location

Pune, Maharashtra, India.

Who Should Apply

This opportunity is suitable for experienced AI engineers, Generative AI developers, AI application engineers, software engineers transitioning into AI engineering, and professionals building enterprise AI platforms. Candidates with 5 to 10 years of experience who have strong Java and Python skills and practical knowledge of LLMs, RAG, AI agents, cloud platforms, and microservices should consider applying.

Professionals with experience in multi-agent systems, AI orchestration, vector search, prompt engineering, LLMOps, MLOps, or AI-assisted software development can bring additional value to the role. Candidates should be comfortable building production solutions rather than focusing only on prototypes.

Career Growth

This role can provide strong exposure to the rapidly evolving AI engineering landscape. Working with LLMs, agentic architectures, RAG systems, cloud platforms, observability, and enterprise automation can help engineers expand their technical depth across both AI and conventional software engineering.

The opportunity to contribute reusable frameworks and best practices can also help experienced engineers develop broader technical influence. Continuous learning, certifications, and exposure to emerging technologies can support long-term growth in AI engineering, solution architecture, and enterprise AI platform development.

Application Advice

When applying, highlight projects where you built or deployed Generative AI applications rather than listing AI technologies without practical examples. Explain your experience with LLM integration, RAG pipelines, vector databases, AI agents, prompt engineering, and enterprise APIs.

Clearly mention your strongest programming languages, cloud platforms, AI frameworks, and DevOps practices. If you have worked with LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, Azure OpenAI, OpenAI, Claude, or Gemini, describe how you used them in real solutions.

Also emphasize experience with production security, governance, monitoring, observability, CI/CD, and responsible AI. Demonstrating measurable outcomes such as improved automation, reduced processing time, better retrieval quality, or increased engineering productivity can make your application stronger.