Forward Deployed Engineer (Immediate Joiners)

Tata Consultancy Services; Chennai District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Tata Consultancy Services seeks experienced AI/ML engineers to design and develop AI-powered prototypes, accelerators, and customer-facing solutions in a cloud-first setup. You will build applications with Gemini APIs, Vertex AI, and Google Cloud services, and craft agentic workflows and AI assistants for diverse use cases.

The role requires hands-on experience with Python, REST/microservices, CI/CD, and production deployment, along with strong stakeholder communication skills and the ability to

Qualifications

• Strong Python programming experience with API development and cloud-native apps.
• Experience building prototypes, accelerators, and enterprise integrations in cloud environments.
• Two years of 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.
• Proficiency 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 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

API development

Cloud-native

GCP

Vertex AI

Gemini APIs

Prompt Engineering

LLM development

Agentic AI

Orchestration

REST APIs

Microservices

Integrations

Containerization

CI/CD

Deployment

Stakeholder communication

Job description

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