

Ampstek
Need USC/GC Only :: Sr./Staff GenAI Engineer - Onsite at NYC
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr./Staff GenAI Engineer, onsite in NYC, with a contract duration of over 6 months. Requires 8+ years (Sr.) or 10+ years (Staff) in ML, 1+ year in LLMs, and proficiency in Python, SQL, and cloud services.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 18, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
New York, United States
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🧠 - Skills detailed
#Langchain #Leadership #ML (Machine Learning) #Python #Data Science #AWS (Amazon Web Services) #Azure #GCP (Google Cloud Platform) #SQL (Structured Query Language) #AI (Artificial Intelligence) #Scala #Deployment #Cloud #Programming
Role description
Position: Sr./Staff GenAI Engineer
Location : Onsite at NYC
Duration: Full Time
Job Description:
8+ years of professional experience in building Machine Learning models & systems for Sr GenAI Engineer and 10+ years for Staff GenAI Engineer
1+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents.
Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must.
Understanding of Cloud services from various cloud services from Azure, GCP, or AWS for building the GenAI applications
Excellent communication skills to effectively collaborate with business SMEs
Roles & Responsibilities
Develop and optimize LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
Codebase ownership: Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
Continuous innovation: Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.
Position: Sr./Staff GenAI Engineer
Location : Onsite at NYC
Duration: Full Time
Job Description:
8+ years of professional experience in building Machine Learning models & systems for Sr GenAI Engineer and 10+ years for Staff GenAI Engineer
1+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents.
Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must.
Understanding of Cloud services from various cloud services from Azure, GCP, or AWS for building the GenAI applications
Excellent communication skills to effectively collaborate with business SMEs
Roles & Responsibilities
Develop and optimize LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
Codebase ownership: Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
Continuous innovation: Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.






