Sr. Gen AI Engineer

• Compensation: USD 110,000 - USD 130,000 - yearly

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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.

• Medical Insurance
• Vision Insurance
• 401(k)
• Paid Sick hours

• 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 product ionize
  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

Required Qualifications

• Bachelor’s 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
  Lang Chain, Llama Index, 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, Tensor Flow, JAX
  , or related ML frameworks
• Experience with
  MLOps
  tools such as MLflow, Sage Maker, 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 company’s long-term Generative AI architecture and roadma

All your information will be kept confidential according to EEO guidelines.