Forward Deployed Engineer(Gemini APIs, Vertex AI, GCP,Python)

Tata Consultancy Services; India; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Tata Consultancy Services in India is seeking a skilled AI engineer to design and develop AI-powered prototypes, accelerators, and customer-facing solutions.

You will build and integrate applications using Gemini APIs, Vertex AI, and Google Cloud services, and develop agentic workflows and multimodal demos for diverse clients. Collaboration with customers, partners, and cross-functional teams is essential to validate use cases and translate requirements into scalable architectures.

Qualifications

• Strong hands-on experience in Python programming, API development, and cloud-native app development (4+ years).
• Experience building prototypes, solution accelerators, and enterprise integrations using cloud tech.
• Two years experience with Google Cloud Platform (GCP), Vertex AI, Gemini APIs, or similar AI platforms.
• Experience in Prompt Engineering, LLM app development, and AI solution implementation.
• Experience developing agentic AI workflows, AI agents, and orchestration frameworks.
• Experience with REST APIs, microservices, and third-party system integrations.
• Experience with containerization, CI/CD, and production deployment practices.
• Strong stakeholder communication and customer-facing solutioning skills.

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

Skills

Python programming

API development

Cloud-native development

GCP

Vertex AI

Gemini APIs

Prompt engineering

LLM development

AI solution implementation

AI workflows

AI agents

Orchestration frameworks

REST APIs

Microservices

Third-party integrations

Containerization

CI/CD

Production deployment

Stakeholder communication

Job description

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