GenAI/Agentic AI Engineer
DATAECONOMY
3 days ago
Full-time
On-site
Boston, Massachusetts, United States
ML & AI Engineering
DATAECONOMY is one of the fastest-growing Data & Analytics company with global presence. We are well-differentiated and are known for our Thought leadership, out-of-the-box products, cutting-edge solutions, accelerators, innovative use cases, and cost-effective service offerings.
We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and Blockchain to large corporates across the globe. Strategic Partners with AWS, Collibra, cloudera, neo4j, DataRobot, Global IDs, tableau, MuleSoft and Talend.
GenAI/Agentic AI Engineer - AWS
Boston, MA/ Charlotte, NCFull-time
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.
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.
· 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.
We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and Blockchain to large corporates across the globe. Strategic Partners with AWS, Collibra, cloudera, neo4j, DataRobot, Global IDs, tableau, MuleSoft and Talend.
GenAI/Agentic AI Engineer - AWS
Boston, MA/ Charlotte, NCFull-time
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.
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.
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.