P
AI Engineer (Agentic AI)
ProwessIT Solutions LLC.
2 hours ago
Full-time
On-site
Shrewsbury, Massachusetts, United States
AI Engineer (Agentic AI)
Location: Remote in US
Duration: Long-term contract
Salary: $120,000/year
Description: We are looking for a hands‑on AI / LLM Engineer to help design and build practical AI-driven solutions within an existing GCP environment. This role will focus on developing real-world use cases using LLMs, RAG architectures, and agentic workflows to enhance internal tools, automation, and data-driven applications.
A strong candidate should be able to:
Clearly explain an AI project they personally worked on.
Explain the business problem/use case behind the project.
Walk through their thought process from requirements through design and implementation.
Explain why they selected specific technologies or architecture.
Discuss their role and contributions without relying on generic or team-level answers.
Think through a new use case logically and build a solution approach.
Communicate confidently and naturally when challenged with follow-up questions.
Must Haves:
Experience with AI/ML and LLMs (OpenAI, Vertex AI, or similar)
Hands‑on experience with RAG (Retrieval‑Augmented Generation)
Strong experience with Google Cloud Platform (BigQuery, Dataflow, Vertex AI preferred)
Experience with AI orchestration tools (LangChain, LlamaIndex, or similar)
Proficiency in Python (preferred) or backend development
Experience with APIs and integrating AI into applications
Nice to Have:
Experience building agent-based or multi-step AI workflows
Familiarity with vector databases (Pinecone, Weaviate, Vertex AI Vector Search)
Background in backend development (Java/Spring Boot)
Experience working in data engineering environments
Key Responsibilities:
Design and build AI/LLM-based solutions, including RAG pipelines
Develop and prototype agentic AI workflows for automation and decisioning
Integrate LLM solutions with existing GCP data platforms (BigQuery, Dataflow)
Work with structured and unstructured data to enable intelligent retrieval and insights
Create, test, and optimize prompt engineering strategies
Collaborate with backend and data engineering teams to embed AI capabilities into applications
+1 (774) 314-9251 #J-18808-Ljbffr
Clearly explain an AI project they personally worked on.
Explain the business problem/use case behind the project.
Walk through their thought process from requirements through design and implementation.
Explain why they selected specific technologies or architecture.
Discuss their role and contributions without relying on generic or team-level answers.
Think through a new use case logically and build a solution approach.
Communicate confidently and naturally when challenged with follow-up questions.
Must Haves:
Experience with AI/ML and LLMs (OpenAI, Vertex AI, or similar)
Hands‑on experience with RAG (Retrieval‑Augmented Generation)
Strong experience with Google Cloud Platform (BigQuery, Dataflow, Vertex AI preferred)
Experience with AI orchestration tools (LangChain, LlamaIndex, or similar)
Proficiency in Python (preferred) or backend development
Experience with APIs and integrating AI into applications
Nice to Have:
Experience building agent-based or multi-step AI workflows
Familiarity with vector databases (Pinecone, Weaviate, Vertex AI Vector Search)
Background in backend development (Java/Spring Boot)
Experience working in data engineering environments
Key Responsibilities:
Design and build AI/LLM-based solutions, including RAG pipelines
Develop and prototype agentic AI workflows for automation and decisioning
Integrate LLM solutions with existing GCP data platforms (BigQuery, Dataflow)
Work with structured and unstructured data to enable intelligent retrieval and insights
Create, test, and optimize prompt engineering strategies
Collaborate with backend and data engineering teams to embed AI capabilities into applications
+1 (774) 314-9251 #J-18808-Ljbffr