Lead I - ML Engineering AI Engineer

Role description Job Title: Senior AI Engineer Experience Range 7+ Years of professional software development experience Hands-on experience building AI/ML or LLM-based enterprise solutions Hiring Location: Hyderabad Must-Have Skills AI / Generative AI Hands-on experience building AI systems using Large Language Models (LLMs) Experience designing and developing: Retrieval-Augmented Generation (RAG) pipelines Agentic AI workflows Multi-model orchestration Experience integrating LLMs with enterprise data and tools Experience with agent frameworks and tool-use/connector patterns (e.g., MCP) Prompt engineering fundamentals AI-assisted development tools (GitHub Copilot, Cursor, etc.) Backend Development Strong backend development experience REST API development Enterprise integration services Modern programming languages/frameworks (Python, Java, Node.js, etc.) Cloud & Platform Cloud-native application development AWS / Azure / GCP Secure application development Authentication & Authorization Secrets management DevOps / CI-CD GitLab CI/CD (or equivalent) Automated build, test, and deployment pipelines AI Observability Structured logging Monitoring AI system performance Cost monitoring Output quality monitoring Tracing & instrumentation Software Engineering Enterprise application architecture Scalable and maintainable software development Technical design Component-level architecture decisions Strong ownership mindset Ability to work in agile environments with evolving requirements Good-to-Have Skills High-throughput distributed systems Low-latency architecture LLM evaluation frameworks AI observability platforms Hallucination detection Agent tracing React / Frontend development AI for log analysis AI-driven anomaly detection Operational intelligence solutions Forward Deployed Engineering (FDE) experience Consulting/customer-facing engineering experience Multi-domain enterprise solution delivery Preferred Technical Stack AI Technologies LLMs RAG Agentic AI Multi-Agent Systems MCP (Model Context Protocol) Prompt Engineering Cloud AWS Azure Google Cloud Platform (GCP) Backend REST APIs Enterprise Integrations Microservices DevOps GitLab CI/CD Automation Pipelines Observability Logging Monitoring Tracing AI Performance Evaluation Key Responsibilities Design and build enterprise-grade AI applications using LLMs. Develop RAG pipelines and agentic AI workflows. Build backend APIs and integration services. Integrate AI capabilities with enterprise systems and data sources. Implement secure, scalable, cloud-native AI solutions. Build and maintain CI/CD pipelines. Monitor AI system performance, cost, and output quality. Apply AI engineering best practices for security, reliability, and compliance. Work closely with product, architecture, and engineering teams to deliver production-ready AI solutions. Skills Agentic AI, CI/CD, LLMs, GitLab, Backend Development, Authentication and Authorization, Cloud Infrastructure, Observability, REST About UST UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the worlds best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients organizations. With over 30,000 employees in 30 countries, UST builds for boundless impacttouching billions of lives in the process. Role description Job Title: Senior AI Engineer Experience Range 7+ Years of professional software development experience Hands-on experience building AI/ML or LLM-based enterprise solutions Hiring Location: Hyderabad Must-Have Skills AI / Generative AI Hands-on experience building AI systems using Large Language Models (LLMs) Experience designing and developing: Retrieval-Augmented Generation (RAG) pipelines Agentic AI workflows Multi-model orchestration Experience integrating LLMs with enterprise data and tools Experience with agent frameworks and tool-use/connector patterns (e.g., MCP) Prompt engineering fundamentals AI-assisted development tools (GitHub Copilot, Cursor, etc.) Backend Development Strong backend development experience REST API development Enterprise integration services Modern programming languages/frameworks (Python, Java, Node.js, etc.) Cloud & Platform Cloud-native application development AWS / Azure / GCP Secure application development Authentication & Authorization Secrets management DevOps / CI-CD GitLab CI/CD (or equivalent) Automated build, test, and deployment pipelines AI Observability Structured logging Monitoring AI system performance Cost monitoring Output quality monitoring Tracing & instrumentation Software Engineering Enterprise application architecture Scalable and maintainable software develo