

Woongjin, INC.
Sr. Gen AI Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr. Gen AI Engineer, with a contract length of over 6 months and a competitive pay rate. Key skills include Python, LLM application development, and experience with cloud platforms. A Bachelor's degree and 5+ years of relevant experience are required.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
590
-
ποΈ - Date
March 11, 2026
π - Duration
More than 6 months
-
ποΈ - Location
Unknown
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π - Contract
Unknown
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π - Security
Unknown
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π - Location detailed
Ridgefield Park, NJ
-
π§ - Skills detailed
#Leadership #MLflow #Azure #Deployment #Cloud #Monitoring #Automation #AWS (Amazon Web Services) #Deep Learning #Generative Models #AI (Artificial Intelligence) #TensorFlow #SaaS (Software as a Service) #Scala #Python #Model Optimization #SageMaker #Security #Programming #GCP (Google Cloud Platform) #Docker #NLP (Natural Language Processing) #PyTorch #Databases #Kubernetes #ML (Machine Learning) #Observability #API (Application Programming Interface) #Elasticsearch #Langchain #Computer Science
Role description
Company Description
For More Open Positions Visit us at: http://recruiting.woongjininc.com/
Our Mission WOONGJIN, Inc. is a rapidly growing team who provides a range of unique, exceptional, and enhanced services to our clients. We have a strong moral code that includes the service of goodness without expectations of reward. We are motivated by the sense of responsibility and servant leadership.
Benefits
Medical Insurance
Vision Insurance
Dental Insurance
401(k)
Paid Sick hours
Job Description
Design and develop algorithms for generative models using deep learning techniques
Design and build LLM-powered applications for internal and/or customer-facing use cases
Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems
Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration
Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate
Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability
Implement prompt engineering, structured outputs, tool calling, and model optimization strategies
Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices
Build monitoring, observability, and feedback loops for model and application performance in production
Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems
Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities
Mentor other engineers and contribute to architecture, technical direction, and engineering best practices
Qualifications
Required Qualifications
Bachelorβs degree in Computer Science, Engineering, Machine Learning, or a related field
5+ years of software engineering, machine/deep learning engineering, or applied AI experience
2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production
Strong programming skills in Python and experience with backend/API development
Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design
Experience in optimizing RAG pipelines using both structured and unstructured data
Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent
Experience in generative AI techniques such as GANs, and VAEs
Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search
Experience with cloud platforms such as AWS, GCP, or Azure
Experience with Docker, Kubernetes, CI/CD, and production deployment practices
Strong understanding of software architecture, scalability, reliability, and distributed systems
Experience building evaluation, testing, and monitoring for AI systems
Strong communication skills and ability to work closely with technical and non-technical stakeholder
Preferred Qualifications
Experience fine-tuning or adapting open-source LLMs
Advanced knowledge of natural language processing for text generation tasks
Experience with PyTorch, TensorFlow, JAX, or related ML frameworks
Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar
Experience building multi-agent systems or advanced orchestration workflows
Experience with AI safety, guardrails, red-teaming, privacy, and governance
Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems
Experience in customer-facing or enterprise SaaS products
Experience in semiconductor/manufacturing, retail and e-commerce sectors
What Success Looks Like
Deliver production-ready GenAI features that improve user experience and business outcomes
Build reliable and scalable AI systems with strong quality, latency, and cost performance
Establish best practices for evaluation, observability, and responsible AI development
Help define the companyβs long-term Generative AI architecture and roadma
Additional Information
All your information will be kept confidential according to EEO guidelines.
β’
β’
β’ NO C2C
β’
β’
β’
Company Description
For More Open Positions Visit us at: http://recruiting.woongjininc.com/
Our Mission WOONGJIN, Inc. is a rapidly growing team who provides a range of unique, exceptional, and enhanced services to our clients. We have a strong moral code that includes the service of goodness without expectations of reward. We are motivated by the sense of responsibility and servant leadership.
Benefits
Medical Insurance
Vision Insurance
Dental Insurance
401(k)
Paid Sick hours
Job Description
Design and develop algorithms for generative models using deep learning techniques
Design and build LLM-powered applications for internal and/or customer-facing use cases
Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems
Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration
Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate
Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability
Implement prompt engineering, structured outputs, tool calling, and model optimization strategies
Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices
Build monitoring, observability, and feedback loops for model and application performance in production
Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems
Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities
Mentor other engineers and contribute to architecture, technical direction, and engineering best practices
Qualifications
Required Qualifications
Bachelorβs degree in Computer Science, Engineering, Machine Learning, or a related field
5+ years of software engineering, machine/deep learning engineering, or applied AI experience
2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production
Strong programming skills in Python and experience with backend/API development
Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design
Experience in optimizing RAG pipelines using both structured and unstructured data
Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent
Experience in generative AI techniques such as GANs, and VAEs
Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search
Experience with cloud platforms such as AWS, GCP, or Azure
Experience with Docker, Kubernetes, CI/CD, and production deployment practices
Strong understanding of software architecture, scalability, reliability, and distributed systems
Experience building evaluation, testing, and monitoring for AI systems
Strong communication skills and ability to work closely with technical and non-technical stakeholder
Preferred Qualifications
Experience fine-tuning or adapting open-source LLMs
Advanced knowledge of natural language processing for text generation tasks
Experience with PyTorch, TensorFlow, JAX, or related ML frameworks
Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar
Experience building multi-agent systems or advanced orchestration workflows
Experience with AI safety, guardrails, red-teaming, privacy, and governance
Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems
Experience in customer-facing or enterprise SaaS products
Experience in semiconductor/manufacturing, retail and e-commerce sectors
What Success Looks Like
Deliver production-ready GenAI features that improve user experience and business outcomes
Build reliable and scalable AI systems with strong quality, latency, and cost performance
Establish best practices for evaluation, observability, and responsible AI development
Help define the companyβs long-term Generative AI architecture and roadma
Additional Information
All your information will be kept confidential according to EEO guidelines.
β’
β’
β’ NO C2C
β’
β’
β’






