Generative AI Engineer - GCP

Who We Are

At UST, we help the world s best organizations grow and succeed through transformation. Bringing together the right talent, tools, and ideas, we work with our clients to co-create lasting change. Together, with over 30,000 employees in 30+ countries, we build for boundless impact-touching billions of lives in the process. Visit us at .

Summary

UST is looking for an experienced Software Engineer - Generative AI GCP with 5-7 years of software engineering experience and strong expertise in Generative AI, LLM integration, agentic AI, Python, and Google Cloud Platform . The ideal candidate will have hands-on experience building enterprise-grade AI applications, RAG solutions, AI agents, and cloud-native architectures using technologies such as Vertex AI, LangChain, Google ADK, MCP, vector databases, and embeddings .

The candidate will be responsible for designing, developing, deploying, and optimizing scalable AI solutions while ensuring security, reliability, governance, and responsible AI practices.

The Opportunity

Key Roles Responsibilities

• Integrate commercial and open-source LLM APIs into enterprise applications and business workflows.
• Design and develop agentic AI workflows using orchestration frameworks such as LangChain and Google ADK.
• Build multi-step AI workflows supporting reasoning, tool usage, workflow orchestration, and autonomous decision-making.
• Develop and optimize prompt engineering strategies to deliver high-quality, reliable, consistent, and secure model outputs.
• Implement and manage Model Context Protocol (MCP) integrations for AI applications and agents.
• Design and develop Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector databases, semantic search, and contextual retrieval.
• Work with transformer-based architectures and modern NLP techniques, including models such as BERT .
• Design highly available, scalable, secure, and resilient cloud-native architectures for enterprise AI workloads.
• Develop and deploy AI solutions using Google Cloud Platform (GCP) , with hands-on experience across Vertex AI, BigQuery, Cloud Storage, Cloud Functions, and Cloud Run .
• Develop Python-based applications following sound software engineering principles, including clean coding, version control, testing, debugging, and maintainability.
• Implement AI security, data privacy, governance, and responsible AI practices across AI solutions.
• Design and implement AI Guardrails to manage model safety, reliability, data protection, and policy compliance.
• Collaborate with cross-functional teams, architects, data scientists, and business stakeholders to translate business requirements into scalable AI solutions.
• Troubleshoot, optimize, and continuously improve AI applications for performance, scalability, cost, and reliability.
• Stay current with emerging developments in Generative AI, LLMs, agentic AI, RAG, AI frameworks, and cloud technologies .

What You Need

Required Skills

• 5-7 years of professional experience in software engineering, AI/ML engineering, or a related field.
• Advanced proficiency in Python and strong software engineering fundamentals.
• Hands-on experience with Generative AI and LLM application development .
• Experience integrating commercial and/or open-source LLM APIs into enterprise applications.
• Strong experience designing and developing AI agents and agentic workflows .
• Hands-on experience with LangChain or similar AI orchestration frameworks.
• Experience with Google ADK and/or equivalent agent development frameworks.
• Experience implementing and managing Model Context Protocol (MCP) integrations.
• Strong understanding of transformer architectures, LLMs, embeddings, NLP, and semantic search .
• Hands-on experience building RAG pipelines using vector databases and embedding models.
• Strong hands-on experience with Google Cloud Platform (GCP) .
• Practical experience with Vertex AI, BigQuery, Cloud Storage, Cloud Functions, and/or Cloud Run .
• Experience implementing AI security, governance, privacy, and responsible AI practices .
• Development experience with AI Guardrails is required.
• Strong understanding of software development lifecycle, version control, testing, debugging, and deployment practices.
• Strong…