GenAI/Agentic AI Engineer
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Summary
Dataeconomy, a data & analytics services firm, seeks a GenAI/Agentic AI Engineer in Rutherford/Jersey City, NJ to independently design and build production-grade generative and agentic AI applications. Day-to-day work centers on Python GenAI libraries (LangChain, LangGraph, CrewAI), RAG/LLM components, and AWS services like Bedrock, integrated with Databricks data pipelines.
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
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
· 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
Skills
- Agentic AI
- AI
- Airflow
- Analytics
- API
- API Gateway
- AWS
- AWS Bedrock
- Big Data
- Blockchain
- Cloud
- Cloudera
- Collibra
- CrewAI
- Data Engineering
- Data Governance
- Databricks
- DevOps
- EC2
- Generative AI
- Lambda
- LangChain
- LangGraph
- LLM
- Machine Learning
- Mulesoft
- Neo4j
- Pydantic
- Python
- RAG
- S3
- Tableau
- Talend
- Vector Databases