Key Facts

Remote From:

Pennsylvania (USA)

Category: AI Specialist

Full time

Senior (5-10 years)

English

Roles & Responsibilities

6–8+ years of software development experience with a focus on AI/ML or LLM integration
Proven experience as an AI integrator—bringing external AI products into internal systems
Strong programming skills in Python
Experience with PyTorch and modern AI/ML frameworks

Requirements:

Lead the migration of an externally developed AI/LLM solution into internal infrastructure
Integrate and adapt LLMs (e.g., OpenAI, Claude, etc.) across enterprise environments
Perform model/platform transitions (e.g., switching LLM providers, Oracle → Snowflake)
Design and develop AI-powered applications, including chatbot/assistant interfaces

Dale WorkForce Solutions

About Dale WorkForce Solutions

Dale Workforce Solutions (DWS) is a WBENC certified woman owned staffing and talent solution leader, providing information technology and professional staffing to a nationwide client base. We strive to EMPOWER change, ENRICH partnerships and ELEVATE outcomes. Mission: To help our clients advance their business culture with exceptional talent through an intentional focus on agility, diversity, and inclusion. We strive to Empower change, enrich partnerships, elevate outcomes Core Values Integrity, Teamwork, Care, and Agility Simplify: Communicate with clarity, focus and purpose Relationships: Act with integrity, value connections, and build trusted partnerships Impact: Make a difference, be passionate, fun and ﬂexible

Company type: SME

Founded: 2018

Company size: 11 - 50

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Job description

Job Title: Senior AI Developer / AI Integrator (LLM, Data Access)
Location: Remote (EST hours required; NJ/NY/PA preferred – proximity to King of Prussia, PA is a plus)
Duration: Contract-to-Hire (6 months+)

Position Overview
We are seeking a Senior AI Developer / Integrator. This role sits at the intersection of AI engineering, system integration, and data governance, with a strong focus on operationalizing LLM-based solutions within internal platforms.

The ideal candidate will have hands-on experience integrating third-party LLM solutions, performing "lift-and-shift” transformations across AI models and data platforms, and building scalable AI applications that support data access, compliance, and business workflows.

Key Responsibilities

Lead the migration of an externally developed AI/LLM solution into internal infrastructure
Integrate and adapt LLMs (e.g., OpenAI, Claude, etc.) across enterprise environments
Perform model/platform transitions (e.g., switching LLM providers, Oracle → Snowflake)
Design and develop AI-powered applications, including chatbot/assistant interfaces
Build and maintain APIs and integrations for AI services and enterprise systems
Enhance model performance through prompt engineering, tuning, and optimization
Work with structured and unstructured data to support data access and decisioning workflows
Collaborate with business stakeholders to translate requirements into AI-enabled solutions
Ensure alignment with data governance, security, compliance, and privacy standards
Stay current with emerging AI technologies and recommend improvements

Required Qualifications

6–8+ years of software development experience with a focus on AI/ML or LLM integration
Proven experience as an AI integrator—bringing external AI products into internal systems
Strong programming skills in Python
Experience with PyTorch and modern AI/ML frameworks
Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.)
Strong SQL/PSQL and data querying skills
Experience building and consuming REST APIs
Familiarity with Snowflake and/or Oracle environments
Experience working in agile, fast-evolving technical environments

Preferred Qualifications

Experience in data governance, data cataloging, or master data management
Knowledge of data access, security, compliance, and privacy frameworks
Experience with pharmaceutical or healthcare datasets
Background building AI chat assistants or data access tools
Exposure to graph-based data integrations
Experience in regulated environments

What Success Looks Like

Successfully internalize and operationalize an AI-powered data access assistant
Seamlessly transition across LLMs and data platforms with minimal disruption
Deliver a scalable, production-ready AI solution aligned to business and compliance needs
Act as a technical lead in shaping AI integration strategy