Compensation
This employer didn't list pay. Model a likely range with the calculator.
Model this offer in the calculatorJob description
Team: IT
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr AI Engineer based in India.
This role is centered on building production-grade AI systems that move beyond experimentation into real-world impact. You will design and deploy intelligent agent-based solutions powered by modern LLM technologies, primarily within enterprise and Azure ecosystems. Working in a fast-paced engineering environment, you will transform complex business challenges into scalable AI applications, including multi-agent systems, RAG pipelines, and tool-augmented workflows. The role requires strong hands-on engineering depth, with a focus on shipping reliable, production-ready AI systems. You will collaborate across teams to integrate AI into enterprise platforms such as Microsoft 365 and Teams, while ensuring robustness, evaluation, and responsible AI practices. This is a highly technical role for engineers who enjoy ownership, rapid execution, and building the next generation of AI-native systems.
Accountabilities:
- Design, build, and deploy AI agents and multi-agent systems using modern frameworks within the Azure ecosystem
- Develop and maintain MCP servers and tool integrations to connect AI agents with enterprise data sources and workflows
- Build RAG pipelines, orchestration patterns, prompt engineering workflows, and evaluation frameworks for LLM-based systems
- Design and expose scalable RESTful APIs to integrate AI capabilities with enterprise platforms such as Microsoft 365 and Teams
- Build and manage data pipelines for unstructured data such as transcripts, customer interactions, and support logs
- Implement CI/CD pipelines, monitoring systems, and responsible AI safeguards for production AI solutions
- Use AI-native development tools (e.g., Copilot CLI, Cursor, Claude Code, agent-based IDEs) as part of daily engineering workflows
- Contribute across infrastructure, low-code agent configuration, and data engineering as needed in a fast-evolving environment
- 7+ years of software engineering experience, including 3+ years working on GenAI/LLM systems in production
- Strong hands-on experience building AI agents using platforms such as Azure AI Foundry, Microsoft Agent Framework, or similar tools
- Deep expertise in LLM engineering, including prompt design, evaluation strategies, structured outputs, and model selection
- Advanced proficiency in Python with experience building scalable, production-grade systems
- Strong experience designing and developing RESTful APIs for enterprise applications
- Solid understanding of Azure cloud services, including deployment, identity, search, and infrastructure components
- Proven experience building RAG systems, orchestration workflows, and tool-augmented AI pipelines
- Hands-on experience with CI/CD, monitoring, and responsible AI implementation in production environments
- Experience working with unstructured data pipelines and large-scale AI system integration
- Strong ownership mindset with the ability to operate independently in ambiguous, fast-moving environments
- Preferred: experience with MCP protocols, LLMOps/evaluation frameworks, PySpark, Copilot Studio, Kubernetes, or enterprise AI integrations
- Competitive compensation aligned with experience and market standards
- Opportunity to work on cutting-edge AI agent and LLM-based production systems
- Fully remote-friendly or flexible work arrangements (depending on project requirements)
- Exposure to enterprise-scale AI deployments within Microsoft ecosystem technologies
- Learning and growth opportunities in GenAI, agentic systems, and cloud-native AI architecture
- Collaborative, innovation-driven engineering culture focused on real-world impact
- Opportunity to work with modern AI development tools and emerging frameworks
- Inclusive and diverse work environment emphasizing collaboration, transparency, and accountability.
Requirements:
Benefits:
Related roles