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AI Solutions Architect at Liberty Home Guard

Brooklyn, NY 11223, USA -

Full Time

Start Date

Immediate

Expiry Date

04 Dec, 25

Salary

120000.0

Posted On

05 Sep, 25

Experience

3 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Finance, Kubernetes, Computer Science, Data Modeling, Python, Nlp, Ownership, Data Integration, Data Engineering, Azure, Aws, Processing, Data Science

Industry

Information Technology/IT

Description

Responsibilities

Architect and implement a secure, private AI infrastructure that serves all Liberty Home Guard employees with real-time, context-specific support across various workstreams.
Build and maintain robust ETL pipelines to connect, clean, and centralize data from disparate sources including claims, customer service, HR, billing, and operational systems.
Develop systems that can extract insights from structured and unstructured data and translate them into usable formats for machine learning, NLP, and AI chatbot applications.
Develop custom models, algorithms, and integrations in Python with external LLMs (e.g., Grok, OpenAI) to support advanced search, automation, and recommendation functionalities tailored to Liberty Home Guard’s operations.
Design and manage a scalable data warehouse that supports rapid querying, integration, and experimentation.Collaborate with internal teams to map out workflows and business logic that will inform AI behavior and use-case prioritization.
Ensure strict adherence to data privacy and security best practices while enabling broad internal usability.
Integrate AI agents and retrieval-augmented generation (RAG) techniques to enable real-time querying of vast datasets, including call transcripts and metrics.
Implement MLOps practices for model deployment, monitoring, and versioning to ensure reliable AI performance.
Incorporate AI ethics and bias mitigation strategies in all models and data pipelines.
Continuously optimize system performance and reliability, with a focus on long-term scalability and maintainability.
Stay up-to-date with the latest developments in AI, large language models (LLMs), and data engineering tools to guide our technical roadmap.
Work closely with QA, product, and leadership to test prototypes, gather feedback, and iterate rapidly.