ML Engineer (NLP/GenAI)

Saur Energy International; Chennai District; On-site; INR 3,600,000 - 6,000,000; Full time

Job summary

Saur Energy International in Chennai, Tamil Nadu, invites an experienced GenAI Engineer to help scale AI-powered digital products. You will drive active development and contribute to valuable AI solutions across the product portfolio.

You will collaborate with product owners, ML engineers and business SMEs to design and deploy GenAI capabilities, including LLM-based workflows, RAG pipelines and tool integrations, while promoting robust NLP practices and agentic system patterns.

Qualifications

• Bachelor’s or master’s degree in CS, Engineering, Data Science, or related field.
• 6+ years in AI/ML, software engineering, data or analytics for digital solutions.
• 2-5 years core AI/ML solution development focusing on NLP and GenAI systems.
• Hands-on with LLM ecosystems (OpenAI, Azure OpenAI) and prompt engineering.
• Experience with RAG architecture, embeddings or vector databases.
• Experience building apps with APIs, microservices or containers.
• Familiarity with version control, testing, and CI/CD basics.
• Exposure to agentic workflows and multi-step reasoning.
• Understanding LLM evaluation and LLMOps basics (monitoring, versioning, cost).

Responsibilities

• Collaborate with product owner, ML engineers, developers and SMEs to develop GenAI capabilities.
• Design, develop and deploy GenAI and agent-based systems for reasoning and semi-autonomous workflows.
• Build GenAI components using LLMs, RAG pipelines, prompt engineering and tool integration.
• Develop intelligent workflows with prompt engineering and context orchestration.
• Integrate GenAI into enterprise apps via APIs, microservices and containers.
• Collaborate with senior AI engineers to implement scalable, reliable GenAI systems.
• Participate in end-to-end delivery including development, testing and deployment.
• Continuously learn best practices in GenAI, NLP and agented systems development.

Skills

LLM ecosystems

Prompt engineering

RAG architecture

Embeddings/Vector databases

APIs & microservices

Containerized environments

Version control & testing

Tool integration

Agentic workflows

LLMOps concepts

Education

Bachelor’s or Master’s degree in CS/Engineering/Data Science

Tools

GitHub Copilot

Claude Code

Job description

Responsibilities

• As part of the product team, you will collaborate with product owner, ML engineers, application developers and business SMEs to develop and scale GenAI and agent-based capabilities within digital products. This role focuses on active development, learning, and contributing to valuable AI solutions
• Contribute to the design, development and deployment of GenAI and agentic systems supporting reasoning, planning, and semi-autonomous workflows
• Build and enhance components of GenAI solutions using LLMs, RAG pipelines, prompt engineering and tool integration
• Develop intelligent workflows using techniques such as prompt engineering, context orchestration and function/tool calling
• Integrate GenAI capabilities into enterprise applications using APIs, microservices, and containerized environments
• Collaborate with senior AI engineers to implement scalable, reliable GenAI systems and follow established design patterns and standards
• Participate in end-to-end delivery of GenAI initiatives, contributing to development, testing and deployment
• Continuously learn and adopt best practices in GenAI, NLP, and agentic systems development

Qualifications

• AI/ML Solutions Experience
  • Bachelor's or Master's degree in Computer Science / Engineering / Data Science / or similar specialization
  • 6+ years of experience in AI/ML, software engineering, data or analytics, focusing on digital solutions development
  • 2-5 years of core experience in AI/ML solution development, ML engineering, with a focus on NLP and applied GenAI systems
  • Practical experience with LLM ecosystems (e.g., OpenAI, Azure OpenAI, open-source models), including prompt engineering and basic context design
  • Practical experience with RAG architecture, embeddings or vector databases
  • Experience building and integrating applications using APIs, microservices or containerized environments
  • Familiarity with software engineering best practices (version control, testing, CI/CD basics)
  • Exposure to agentic workflows, including tool usage, chaining, or multi-step reasoning
  • Familiarity with LLM evaluation concepts and basic understanding of LLMOps practices such as monitoring, versioning, and cost awareness

Competencies

• LLM Systems Engineering
  • Ability to contribute to building scalable and reliable GenAI systems with focus on performance and maintainability o Understanding of standard design patterns and engineering practices for LLM-based applications
  • Familiarity with deploying and integrating GenAI solutions into production environments
• GenAI & Agentic Solution Development
  • Practical experience in developing GenAI and agent-based solutions for structured workflows and assisted decision‑making
  • Working knowledge of techniques such as RAG, prompt engineering and tool integration
  • Ability to implement intelligent workflows combining human-in-the-loop and automated processes under guidance
• Foundational AI/ML & Software Engineering
  • Solid foundation in ML concepts and software engineering principles for building maintainable systems
  • Experience developing and integrating services using APIs, microservices and modern engineering practices
  • Proficiency in leveraging AI-assisted development tools (e.g., GitHub Copilot, Claude Code) to improve productivity and code quality
• Global Collaboration & Enablement
  • Ability to collaborate effectively within distributed teams across geographies
  • Solid teamwork skills working with senior engineers and cross‑functional stakeholders
  • Demonstrates a continuous learning mindset with interest in GenAI, NLP and agentic systems