Sr AI Engineer

Hi,

Our client is an India's marquee global technology company. They are an international flag-bearer of technical and managerial excellence. With offices around the globe, the company has a comprehensive presence across multiple segments of the IT product and service industries.

The Job

We are looking for a Senior AI Engineer to design, build, and operate production-grade AI applications. In this role, you will develop backend services and APIs that integrate large language models into business workflows, with a strong focus on reliability, safety, observability, and maintainability. Strong software engineering fundamentals and hands-on experience delivering LLM-powered systems to production. You should be comfortable owning services end to end, adapting them as models and requirements evolve, and helping teams adopt effective AI engineering practices.

• Build and operate production-grade AI services and backend applications in Python
• Design and implement LLM-powered workflows, including prompt design, context management, structured outputs, and tool calling
• Define robust contracts for APIs and AI outputs
• Test, evaluate, and improve AI services through automated testing, prompt iteration, and measurable evaluation approaches
• Implement safety and reliability controls such as validation, guardrails, fallbacks, and error handling
• Monitor and improve production systems using logs, metrics, traces, and AI observability tooling
• Work closely with engineers, product owners, and domain stakeholders to turn ambiguous use cases into production-ready solutions.
• Continuously improving systems through model upgrades, prompt iteration, and operational optimization.

Your Profile

• 7+ years of Strong Python and backend engineering skills for building production-grade services and APIs.
• Proven experience developing and shipping LLM-powered applications in production.
• Strong understanding of prompt engineering, structured outputs, context management, and tool calling.
• Experience integrating foundation models and LLM platforms such as Azure OpenAI, OpenAI, or Bedrock.
• Strong experience in API design, testing, deployment discipline, observability, evaluation, and failure handling.
• Solid practical understanding of AI safety, reliability, and evaluation, including guardrails, fallback patterns, and output validation.
• A pragmatic approach to solving messy real-world problems with clean, maintainable systems.
• Experience designing and operating LLM systems with orchestration frameworks such as LangChain, MCP, RAG, Graph databases.
• Familiarity with platform engineering practices such as Infrastructure as Code and performance testing for production APIs.
• Experience working with Java or Kotlin.