Tata Consultancy Services
Forward Deployed Engineer(Gemini APIs, Vertex AI, GCP,Python)
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
India
Work mode:
Onsite
Published on:
8 September 2026
What they need
Must Have Technical/Functional Skills
- Must have strong hands-on experience in Python programming, API development,
and cloud-native application development (4 Years Minimum).
- Must have experience building prototypes, solution accelerators, and enterprise integrations
using cloud technologies.
- Must have two years experience with Google Cloud Platform (GCP), Vertex AI, Gemini APIs,
or similar AI platforms.
- Must have experience in Prompt Engineering, LLM application development, and AI solution implementation.
- Must have experience developing Agentic AI workflows, AI agents, and orchestration frameworks.
- Must have experience with REST APIs, microservices, and third-party system integrations.
- Must have experience working with containerization, CI/CD, and production deployment practices.
- Must possess strong stakeholder communication and customer-facing solutioning skills
Preferred Skills (Good to Have)
- Excellent communicator with a consulting mindset – articulate, conversant, and able to engage business and technical stakeholders with clarity and confidence.
- Hands-on experience with Gemini Enterprise, and skilled in Gemini Enterprise for Customer Experience (GECX).
- Well versed in the Telecommunications domain (added advantage).
Roles & Responsibilities
- Design and develop AI-powered prototypes, accelerators, and customer-facing solutions.
- Build and integrate applications using Gemini APIs, Vertex AI, and Google Cloud services.
- Develop agentic workflows, AI assistants, and multimodal solution demonstrations.
- Collaborate with customers, partners, and cross-functional teams to validate business use cases.
- Translate business requirements into scalable technical architectures and solutions.
- Build Proof of Concepts (PoCs) and demonstrate business value through rapid prototyping.
- Support deployment, optimization, and troubleshooting of AI solutions in cloud environments.
- Stay current with emerging AI technologies and apply them to customer scenarios
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