- DATAECONOMY
- Rutherford, NC
- Full-Time
- 64 days ago
GenAI/Agentic AI Engineer.
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GenAI/Agentic AI Engineer: our view in 3 lines...
- The Role:This role is for an engineer building GenAI and agentic AI applications using cloud technologies and LLM-based approaches.
- The Person:The person will design and build production-grade GenAI and Agentic AI applications, develop AI pipelines, integrate data with Databricks and AWS services, and suggest improvements to existing application infrastructure.
- Requirements:The ideal candidate has around 5+ years of total experience, 2+ years as a GenAI/Agentic AI engineer, strong Python programming skills, and experience with Databricks, AWS, and GenAI components such as RAG and vector databases.
About the role
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
Rutherford, NJ/ Jersey City, NJ
AI Engineer
Rutherford, NJ/ Jersey City, NJ
Full-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.
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.,).
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.
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.,).
· 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
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
​· 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.
· 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.
Benefits
Standard full-time benefits