AI Full Stack Engineer

Jobtailor; Chennai District; On-site; INR 900,000 - 1,400,000; Full time

Job summary

Jobtailor invites an experienced AI Architect to design, develop, and deploy production-grade AI infrastructure and ML models at scale in Chennai. You will own end-to-end AI workflows, build robust data pipelines, optimize performance and cost, and collaborate with stakeholders across global teams.

The role requires in-depth Python, NLP, CV, and cloud platform expertise, with hands-on LLMs and RAG/Agentic AI experience.

Qualifications

• Bachelor’s degree with 5–8 years in AI architecture or ML development.
• Proficiency in Python, AI/ML algorithms, NLP, Computer Vision, and cloud AI platforms (e.g., Vertex-AI).
• Expertise in Agentic AI, RAG, MCP tools, and frameworks like LangChain or LlamaIndex.
• Hands‑on experience with LLMs (GPT, Claude, Llama) and fine‑tuning models for custom production datasets.
• Experience with Docker, Kubernetes, and building robust API frameworks.
• Proficiency in SQL, NoSQL, Graph, and Vector databases (e.g., BigQuery, Databricks).
• Strong Agile knowledge, requirement gathering, and the ability to manage global stakeholders through clear communication and problem‑solving.
• Excellent stakeholder management and business engagement skills.
• Any AI related certifications.
• Experience in the Automotive industry and related compliance domains.
• Specific exposure to GCP data services (Cloud SQL, Postgres).

Responsibilities

• Design, develop, and deploy production-ready AI infrastructure and ML models.
• Architect Agentic AI workflows and RAG systems for enterprise use cases.
• Build high-performance, scalable data pipelines to support AI/ML model training and inference.
• Develop and implement solutions leveraging Generative AI, Computer Vision, and NLP.
• Optimize model performance, latency, and cost for production environments.
• Stay current with emerging AI/ML frameworks, tools, and best practices.
• Design and develop front-end and back-end components to support production applications.
• Build robust APIs and integrate AI/ML models into web and enterprise applications.
• Ensure application scalability, security, and performance across the stack.
• Provide ongoing production support for Production applications, including troubleshooting, root cause analysis, and issue resolution.
• Monitor application health, performance, and reliability post-deployment.
• Create and maintain support documentation, runbooks, and knowledge base articles.
• Respond to incidents and manage escalations in a timely manner.

Skills

AI architecture

ML development

Data pipelines

Model optimization

API development

SQL proficiency

NoSQL proficiency

Graph database

Vector database

Agile methodologies

Stakeholder management

Clear communication

Problem-solving

Education

Bachelor’s degree

AI related certifications

Tools

Vertex AI

LangChain

LlamaIndex

Docker

Kubernetes

BigQuery

Databricks

Cloud SQL

Postgres

Job description

• Design, develop, and deploy production-ready AI infrastructure and machine learning models
• Architect Agentic AI workflows and RAG systems for enterprise use cases
• Build high-performance, scalable data pipelines to support AI/ML model training and inference
• Develop and implement solutions leveraging Generative AI, Computer Vision, and NLP
• Optimize model performance, latency, and cost for production environments
• Stay current with emerging AI/ML frameworks, tools, and best practices
• Design and develop front-end and back-end components to support production applications
• Build robust APIs and integrate AI/ML models into web and enterprise applications
• Ensure application scalability, security, and performance across the stack
• Provide ongoing production support for Production applications, including troubleshooting, root cause analysis, and issue resolution
• Monitor application health, performance, and reliability post-deployment
• Create and maintain support documentation, runbooks, and knowledge base articles
• Respond to incidents and manage escalations in a timely manner

Requirements

• Bachelor’s degree with 5–8 years in AI architecture or ML development.
• Proficiency in Python, AI/ML algorithms, NLP, Computer Vision, and cloud AI platforms (e.g., Vertex-AI).
• Expertise in Agentic AI, RAG, MCP tools, and frameworks like LangChain or LlamaIndex.
• Hands‑on experience with LLMs (GPT, Claude, Llama) and fine‑tuning models for custom production datasets.
• Experience with Docker, Kubernetes, and building robust API frameworks.
• Proficiency in SQL, NoSQL, Graph, and Vector databases (e.g., BigQuery, Databricks).
• Strong Agile knowledge, requirement gathering, and the ability to manage global stakeholders through clear communication and problem‑solving.
• Excellent stakeholder management and business engagement skills.
• Any AI related certifications.
• Experience in the Automotive industry and related compliance domains.
• Specific exposure to GCP data services (Cloud SQL, Postgres).

Core Competencies

Demonstrates expertise in designing and deploying AI infrastructure and machine learning models, with a strong focus on optimizing performance and scalability. Proficient in leveraging Generative AI, Computer Vision, and NLP, while ensuring robust API integration and production support.

Highest-signal resume keywords

• Python Proficiency
• AI/ML Algorithms
• NLP Expertise
• Cloud AI Platforms
• Docker and Kubernetes Experience

ATS Optimization Keywords

Hard Skills

• AI Architecture
• Machine Learning Development
• Data Pipeline Development
• Model Optimization
• API Development
• SQL Proficiency
• NoSQL Proficiency
• Graph Database Experience
• Vector Database Experience
• Agile Methodologies

Soft Skills

• Stakeholder Management
• Clear Communication
• Problem-Solving

Certifications & Qualifications

• AI Related Certifications

Industry Keywords

• Automotive Industry
• Compliance Domains

Tools & Technologies

• Vertex-AI
• LangChain
• LlamaIndex
• BigQuery
• Databricks
• Cloud SQL
• Postgres