Google Agent development

Greetings from TCS!!!

TCS is hiring for Google Agent Development

Experience: 5-8 years

Location: PAN India

Skills:

• Google Agent Development Kit (ADK):

  Hands-on experience building intelligent agents using Google’s specialized toolkit, enabling advanced workflow automation and conversational interfaces.

• Python Programming:

  Proficient in writing robust, scalable, and efficient code for AI applications, data analysis, and system integrations.

• Google Gemini Enterprise:

  Expertise in leveraging Gemini’s AI platform to develop and deploy enterprise-grade AI agents that address real-world business challenges.

• Google Vertex AI:

  Skilled in utilizing Vertex AI for managing machine learning models, streamlining workflows from training to deployment and monitoring.

• Prompt Engineering Experience:

  Ability to craft precise and effective prompts to optimize AI agent responses and behaviors for diverse use cases.

• Google BigQuery:

  Experience with data warehousing, analysis, and querying large-scale datasets to support AI-driven insights.

You will play a crucial role in designing, developing, and deploying production-ready AI solution agents. Using the Google AI stack—including Gemini Enterprise and the Google Agent Development Kit (ADK)—you will work within the company’s enterprise ecosystem to create solutions that directly address client needs.

• Collaborative AI Use Case Delivery: Work closely with clients to identify high-impact AI opportunities in supply chain and inventory management (SCR/SCM) for APITV, utilizing agile methodologies to iterate quickly and deliver value.
• Technical Guidance Across Teams: Serve as a trusted advisor for vertical business teams, providing hands-on support and guidance to facilitate the smooth integration and adoption of AI solutions throughout various business units.

Key Responsibilities

• AI Agent Development & Optimization: Build and refine AI agents using the Google AI stack (e.g., Gemini Enterprise), always prioritizing scalability, security, and compliance with enterprise standards.
• End-to-End Solution Implementation: Lead AI initiatives from initial design through to deployment, working in tandem with cross-functional teams—including engineers, data scientists, and business stakeholders—to ensure successful project outcomes.
• Mentorship & Best Practices: Mentor vertical teams on their AI journey by sharing best practices, offering architectural recommendations, and imparting technical expertise to foster innovation and continuous improvement.