

LLM Engineer
β - Featured Role | Apply direct with Data Freelance Hub
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
680
-
ποΈ - Date discovered
September 9, 2025
π - Project duration
Unknown
-
ποΈ - Location type
Unknown
-
π - Contract type
Unknown
-
π - Security clearance
Unknown
-
π - Location detailed
Greater Boston
-
π§ - Skills detailed
#Debugging #Flask #ML (Machine Learning) #Data Science #Kubernetes #Python #Microservices #REST API #Langchain #FastAPI #Security #NLP (Natural Language Processing) #REST (Representational State Transfer) #AI (Artificial Intelligence) #Docker #Deployment
Role description
Insight Global is seeking an LLM Engineer to join our clients dynamic development team. This individual will enhance and expand a complex application, requiring strong communication skills and full-stack technical expertise. This role involves collaborating with global teams across multiple time zones (IST, UST, and other countries) and actively contributing to ongoing feature development.
Key Responsibilities:
β’ Enhance and expand a complex, dynamic application.
β’ Collaborate with global teams across multiple time zones.
β’ Actively contribute to ongoing feature development. Ideal Candidate:
β’ Highly skilled Senior Python and LLM engineer.
β’ Capable of executing both planning and hands-on technical work independently.
β’ Effective collaborator with Product Owners and other stakeholders to solve complex problems.
β’ Able to work cross-functionally to deliver impactful solutions.
β’ Committed to continuously developing technical expertise and staying current with new technologies.
β’ Passionate, intellectually curious, and driven to expand skills and knowledge.
β’ Utilizes a data-driven approach to solve technical challenges and make informed decisions.
β’ Applies systems-level thinking, integrating data science and engineering principles.
β’ Takes full ownership of features and projects, delivering high-quality solutions independently.
REQUIRED SKILLS AND EXPERIENCE
Years of Experience:
β’ 2+ years of experience developing and experimenting with LLMs
β’ 8+ years of experience developing APIs with Python
β’ Background:
β’ Extensive experience with Python, particularly in building REST APIs using frameworks like FastAPI or Flask.
β’ Expertise in microservices architecture and deployment in containerized environments (e.g., Docker, Kubernetes).
β’ Strong knowledge in AI, machine learning, and natural language processing.
β’ Proficient in working with key LLM model APIs (e.g., OpenAI, Anthropic) and LLM frameworks (e.g., LangChain, LlamaIndex).
β’ Experience with MCP (Model Context Protocol).
β’ Understanding of multi-agent systems and their applications in complex problem-solving scenarios.
β’ Familiarity with RAG concepts and fundamentals (vectorDBs, semantic search, etc.).
β’ Expertise in implementing RAG systems that combine knowledge bases with generative AI models.
β’ Skilled in prompt writing for various use cases.
β’ Experience with deploying generative solutions to production at scale, beyond POCs.
β’ Proficiency with server-side events, event-driven architectures, and messaging systems.
β’ Strong problem-solving skills and experience in debugging and optimizing backend systems.
β’ Solid understanding of security best practices for backend systems, including authentication and data protection.
β’ Can work IST and UST hours
Compensation: $65/hr to $85/hr.
Exact compensation may vary based on several factors, including skills, experience, and education. Employees in this role will enjoy a comprehensive benefits package starting on day one of employment, including options for medical, dental, and vision insurance. Eligibility to enroll in the 401(k) retirement plan begins after 90 days of employment. Additionally, employees in this role will have access to paid sick leave and other paid time off benefits as required under the applicable law of the worksite location.
Insight Global is seeking an LLM Engineer to join our clients dynamic development team. This individual will enhance and expand a complex application, requiring strong communication skills and full-stack technical expertise. This role involves collaborating with global teams across multiple time zones (IST, UST, and other countries) and actively contributing to ongoing feature development.
Key Responsibilities:
β’ Enhance and expand a complex, dynamic application.
β’ Collaborate with global teams across multiple time zones.
β’ Actively contribute to ongoing feature development. Ideal Candidate:
β’ Highly skilled Senior Python and LLM engineer.
β’ Capable of executing both planning and hands-on technical work independently.
β’ Effective collaborator with Product Owners and other stakeholders to solve complex problems.
β’ Able to work cross-functionally to deliver impactful solutions.
β’ Committed to continuously developing technical expertise and staying current with new technologies.
β’ Passionate, intellectually curious, and driven to expand skills and knowledge.
β’ Utilizes a data-driven approach to solve technical challenges and make informed decisions.
β’ Applies systems-level thinking, integrating data science and engineering principles.
β’ Takes full ownership of features and projects, delivering high-quality solutions independently.
REQUIRED SKILLS AND EXPERIENCE
Years of Experience:
β’ 2+ years of experience developing and experimenting with LLMs
β’ 8+ years of experience developing APIs with Python
β’ Background:
β’ Extensive experience with Python, particularly in building REST APIs using frameworks like FastAPI or Flask.
β’ Expertise in microservices architecture and deployment in containerized environments (e.g., Docker, Kubernetes).
β’ Strong knowledge in AI, machine learning, and natural language processing.
β’ Proficient in working with key LLM model APIs (e.g., OpenAI, Anthropic) and LLM frameworks (e.g., LangChain, LlamaIndex).
β’ Experience with MCP (Model Context Protocol).
β’ Understanding of multi-agent systems and their applications in complex problem-solving scenarios.
β’ Familiarity with RAG concepts and fundamentals (vectorDBs, semantic search, etc.).
β’ Expertise in implementing RAG systems that combine knowledge bases with generative AI models.
β’ Skilled in prompt writing for various use cases.
β’ Experience with deploying generative solutions to production at scale, beyond POCs.
β’ Proficiency with server-side events, event-driven architectures, and messaging systems.
β’ Strong problem-solving skills and experience in debugging and optimizing backend systems.
β’ Solid understanding of security best practices for backend systems, including authentication and data protection.
β’ Can work IST and UST hours
Compensation: $65/hr to $85/hr.
Exact compensation may vary based on several factors, including skills, experience, and education. Employees in this role will enjoy a comprehensive benefits package starting on day one of employment, including options for medical, dental, and vision insurance. Eligibility to enroll in the 401(k) retirement plan begins after 90 days of employment. Additionally, employees in this role will have access to paid sick leave and other paid time off benefits as required under the applicable law of the worksite location.