AI Specialist / Developer
3B Staffing LLC, Boston, MA, United States
AI Specialist (2-3 Openings)
Location :
Remote, just need to work EST Hours
Duration : 6+ months, extensions are possible.
*** LinkedIn Profiles are Required! ***
This client is looking for 2-3 resources to work on efforts to automate IAM efforts using AI tools.
The Role:
We're looking for strong, hands-on AI Architects with deep experience in Generative AI (GenAI) and (ideally) a strong foundation in Identity and Access Management (IAM).
This role is pivotal in building advanced AI-powered copilot agents with automation capabilities across provisioning, monitoring, threat detection, and response.
Ideal candidates are those who can architect and build, not just ideate-this is not about assembling tools, but understanding and applying GenAI concepts at a deep technical level.
Key Responsibilities
Design and build AI copilot agents leveraging GenAI frameworks
Implement solutions using RAG (Retrieval-Augmented Generation) and Vector Store methodologies
Develop and expose FAST and REST APIs
Collaborate with data scientists and engineering teams to build intelligent, scalable systems
They will Architect AI automation solutions for these 4 IAM workflows:
Provisioning
Monitoring
Threat Detection
Incident Response
Required Skills & Experience
Proven hands-on experience in Generative AI/Conversational AI (e.g., building copilots, fine-tuning LLMs)
Deep knowledge of IAM systems and AI-driven automation
Expertise in:
RAG architecture: RAG is a way of making AI (like ChatGPT-style models) smarter and more accurate by letting it pull in data from outside sources while answering questions.
Large language models (LLMs) like GPT can forget details or not have the latest data. RAG helps fix this by combining search and generation.
It lets the AI "look things up" in real time (from databases, documents, etc.) and use that info in its answers.
Vector databases (e.g., FAISS, Pinecone, Weaviate)
Python (primary language)
REST APIs
Familiarity with Java is a plus, but most work will be in Python
Ability to operate at the Architect level while remaining technically hands-on
Preferred Qualifications
Experience integrating GenAI into cybersecurity or IAM platforms
Familiarity with tools like LangChain, LlamaIndex, or OpenAI APIs
Understanding of modern MLOps and scalable AI infrastructure
Location :
Remote, just need to work EST Hours
Duration : 6+ months, extensions are possible.
*** LinkedIn Profiles are Required! ***
This client is looking for 2-3 resources to work on efforts to automate IAM efforts using AI tools.
The Role:
We're looking for strong, hands-on AI Architects with deep experience in Generative AI (GenAI) and (ideally) a strong foundation in Identity and Access Management (IAM).
This role is pivotal in building advanced AI-powered copilot agents with automation capabilities across provisioning, monitoring, threat detection, and response.
Ideal candidates are those who can architect and build, not just ideate-this is not about assembling tools, but understanding and applying GenAI concepts at a deep technical level.
Key Responsibilities
Design and build AI copilot agents leveraging GenAI frameworks
Implement solutions using RAG (Retrieval-Augmented Generation) and Vector Store methodologies
Develop and expose FAST and REST APIs
Collaborate with data scientists and engineering teams to build intelligent, scalable systems
They will Architect AI automation solutions for these 4 IAM workflows:
Provisioning
Monitoring
Threat Detection
Incident Response
Required Skills & Experience
Proven hands-on experience in Generative AI/Conversational AI (e.g., building copilots, fine-tuning LLMs)
Deep knowledge of IAM systems and AI-driven automation
Expertise in:
RAG architecture: RAG is a way of making AI (like ChatGPT-style models) smarter and more accurate by letting it pull in data from outside sources while answering questions.
Large language models (LLMs) like GPT can forget details or not have the latest data. RAG helps fix this by combining search and generation.
It lets the AI "look things up" in real time (from databases, documents, etc.) and use that info in its answers.
Vector databases (e.g., FAISS, Pinecone, Weaviate)
Python (primary language)
REST APIs
Familiarity with Java is a plus, but most work will be in Python
Ability to operate at the Architect level while remaining technically hands-on
Preferred Qualifications
Experience integrating GenAI into cybersecurity or IAM platforms
Familiarity with tools like LangChain, LlamaIndex, or OpenAI APIs
Understanding of modern MLOps and scalable AI infrastructure