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 world’s 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 impact—touching billions of lives in the process.
