AWS AI Lead

Sonata Software; Bengaluru; Hybrid; INR 3,000,000 - 4,200,000; Full time

Benefits offered by this job

AWS Certification

AWS Specialist Training

Career Growth

Job summary

Sonata Software is seeking an AWS AI Lead to head the delivery of AI, ML, and GenAI initiatives from Bengaluru. The role coordinates engineers, aligns technical outcomes with business needs, and ensures high-quality solution delivery.

The candidate will drive adoption of AWS Bedrock and SageMaker, manage backlogs, and mentor teams while guiding responsible AI safeguards and performance considerations.

Qualifications

• B.E./B.Tech./M.Tech/MCA or equivalent degree in Computer Science, Information Technology, Engineering or related discipline.
• Hands-on delivery experience aligned to the stated experience range and role scope.
• Experience leading AI/ML/GenAI initiatives and solution delivery.
• Strong knowledge of AWS AI services, Bedrock and SageMaker.

Responsibilities

• Lead AI/ML/GenAI implementation squads.
• Translate business problems into AI use cases and implementation backlogs.
• Review models, prompts, RAG flows, evaluation, security and observability.
• Coordinate across architects, data engineers, application teams and business stakeholders.
• Coach engineers and contribute reusable AI patterns and accelerators.

Skills

Amazon Bedrock

Amazon SageMaker

RAG

Prompt engineering

Python

Model evaluation

Education

Bachelor's / Master in CS/IT/Engineering

Tools

LangChain

LlamaIndex

MLOps

APIs

Job description

AWS AI Lead

Location: In office / Hybrid

Work Location: bengaluru

Experience Range

6 to 10 years

Competency Area

AWS AI / ML / GenAI

Role Summary

The AWS AI Lead will lead delivery of AI, ML and GenAI use cases by coordinating engineers, reviewing solution quality and aligning technical outcomes to business needs.

Required Primary Skills

• Amazon Bedrock
• Amazon SageMaker
• RAG
• Prompt engineering
• Python
• Model evaluation

Secondary Skills

• Vector databases
• LangChain / LlamaIndex
• MLOps
• Responsible AI guardrails
• API integration

Technical Skills

• Bedrock, SageMaker and c service integration
• RAG, embeddings, vector databases and foundation model concepts
• Python, APIs, model evaluation and MLOps fundamentals
• Responsible AI, guardrails, security and performance considerations

Key Responsibilities

• Lead AI / ML / GenAI implementation squads.
• Translate business problems into AI use cases and implementation backlogs.
• Review models, prompts, RAG flows, evaluation, security and observability.
• Coordinate across architects, data engineers, application teams and business stakeholders.
• Coach engineers and contribute reusable AI patterns and accelerators.

Preferred Certifications

• AWS Certified AI Practitioner
• AWS Certified Machine Learning Engineer - Associate
• AWS Certified Solutions Architect - Associate

Expected Deliverables

• AI solution design and technical backlog
• Model / prompt evaluation evidence
• Reusable AI patterns and accelerators
• Delivery and quality tracking

Qualification

• B.E. / B.Tech / M.Tech / MCA or equivalent degree in Computer Science, Information Technology, Engineering or related discipline.
• Hands-on delivery experience aligned to the stated experience range and role scope.

Good to have

• AWS certification or active AWS certification plan.
• Experience in reusable assets, accelerators, cloud competency building, customer workshops or proposal support.