Lead AI Developer at Chennai

Global Healthcare Billing Partners; Chennai; Sur place; INR 4 000 000 - 7 000 000; Plein temps

Résumé du poste

Global Healthcare Billing Partners Pvt Ltd seeks a Lead AI Engineer to drive end-to-end AI programs, architecture, and platform design. You will mentor teams, engage stakeholders, and deliver scalable GenAI solutions leveraging LLMs, RAG, and MLOps.

The role requires 8+ years in AI/ML with cloud platforms such as Azure, Vertex AI, Databricks, and AWS, and a strong focus on governance and Responsible AI.

Qualifications

• 8+ years of experience in AI/ML, GenAI, and solution architecture.
• Experience in AI platform design and stakeholder management.
• Azure AI Engineer, Vertex AI, Databricks or AWS certifications.

Responsabilités

• Lead end-to-end delivery of enterprise AI, ML, and Generative AI programs.
• Define AI strategy, architecture standards, and best practices.
• Translate business requirements into scalable AI solutions.
• Design and implement GenAI solutions using LLMs and RAG.
• Build Agentic AI and multi-agent systems for enterprise automation.
• Develop reusable AI accelerators, frameworks, and templates.

Connaissances

Solution Architecture

Technical Leadership

Stakeholder Management

Team Mentoring

Pre-sales and Proposal Support

Formation

Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field

Outils

Azure AI

Google Vertex AI

Databricks

AWS certifications

Description du poste

Greetings From Global Healthcare Billing Partners Pvt Ltd !!

Hiring: Lead AI Engineer

Position: Lead AI Engineer

Experience: 8 to 11 Years

Reporting To: Lead AI Engineer

Location: Chennai

Employment Type: Full-Time

About the Role.

The ideal candidate will Lead AI Engineer to drive the design, architecture, and delivery of enterprise-scale AI and Generative AI solutions. The ideal candidate will lead AI initiatives, mentor engineering teams, engage with stakeholders, and build scalable AI platforms leveraging LLMs, Agentic AI, MLOps, and cloud-native architectures.

Key Responsibilities

AI Solution Leadership

• Lead end-to-end delivery of enterprise AI, ML, and Generative AI programs.
• Define AI strategy, architecture standards, and best practices.
• Translate business requirements into scalable AI solutions.

Generative AI & Agentic AI

• Design and implement advanced GenAI solutions using LLMs and RAG frameworks.
• Build Agentic AI and Multi-Agent Systems for enterprise automation.
• Develop reusable AI accelerators, frameworks, and solution templates.

Architecture & Platform Engineering

• Architect scalable AI platforms leveraging Azure AI, Vertex AI, Databricks, and MLOps frameworks.
• Define governance, monitoring, security, and Responsible AI standards.
• Drive cloud optimization and AI infrastructure scalability.

Client & Business Engagement

• Participate in solutioning, RFP responses, effort estimation, and technical proposals.
• Conduct client workshops, demonstrations, and architecture reviews.
• Identify opportunities to leverage AI for business transformation.

Leadership & Team Management

• Mentor AI Engineers and Data Scientists.
• Lead technical reviews and establish engineering standards.
• Support hiring, capability development, and innovation programs.

LLMs, RAG, Agentic AI, Multi-Agent Systems

• LangChain, LangGraph, CrewAI, AutoGen
• MLflow, Databricks, MLOps
• Python, PyTorch, TensorFlow
• Azure AI, Azure OpenAI, GCP Vertex AI, AWS AI Services
• LLMs, RAG, Agentic AI, Multi- Agent Systems

COMPETENCIES / SKILL SET

Leadership Skills

• Solution Architecture
• Technical Leadership
• Stakeholder Management
• Team Mentoring
• Pre-sales and Proposal Suppor

QUALIFICATIONS & WORK EXPERIENCE

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
• 8+ years overall experience, with strong expertise in AI/ML, Generative AI, solution architecture, AI platform design, stakeholder management, and team mentoring.
• Azure AI Engineer, Google Vertex AI, Databricks, or AWS certifications.

Experience leading enterprise AI transformation initiatives.

PRACTICAL PRODUCTION EXPERIENCE

Prompt engineering and prompt evaluation

RAG pipeline implementation

Vector database integration

LLM output validation

AI response accuracy testing

Logging, monitoring, and cost control

Data privacy and responsible AI practices