GenAI/Agentic AI Developer

Education and experience Qualification 

·        Bachelor's degree in computer science, Information Systems, or
equivalent education or work experience.

·        Around 5+ years of total experience and 2+ years as GenAI/Agentic AI engineer using cloud technologies.

·        Any AWS and/or Databricks certification will be a plus.

Roles & Responsibilities 

·        Should be able to work
independently with minimal directions and guide the team.

·        Researching, learning, and
applying new tools and techniques rapidly and suggesting new concepts to
improve performance. 

·        Recognize the current
application infrastructure and suggest new concepts to improve performance.

·        Design and build production
grade and secure GenAI and Agentic AI applications.

·        Produce reusable, efficient,
and scalable programs, and also cost -effective strategies.

·        Develop AI pipelines and
integrate with the data in Databricks and leverage different AWS services,
including S3, EC2, API Gateway, Bedrock and Lambda.

·        Comfortable to work on tight
timelines, when required.

Requirements

Skill Sets
Required

·        Good decision -making and problem -solving skills.

·        Strong expertise in Python programming with specialization
using various GenAI and Agentic libraries (LangChain, LangGraph, Pydantic,
Strands, CrewAi etc.,).

·        Familiarity of Databricks fundamentals/architecture
and AWS Bedrock, EC2, Postgress and other key services

·        Solid and proven experience in building GenAI and Agentic
AI applications using LLM.

·        Solid knowledge of GenAI components such as RAG, Vector
Database, Model selection, Model evaluations, Guardrails etc.,

·        Good Understanding of GenAI/Agentic AI model architecture
best practices

·        Hands -on experience in different domains, like database
architecture, artificial intelligence, advanced analytics, big data, etc.

Nice to have Skill Sets

·        Knowledge of Databricks, Apache Airflow.

·        Knowledge of Machine Learning.

·        Solid knowledge on CI/CD pipelines in AWS technologies.

·        Finance and Compliance domain knowledge.