Sr. Gen AI Engineer

Sr. Gen AI Engineer Contract

Compensation:

USD 110,000 - USD 130,000

- yearly 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 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 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 company's long-term Generative AI architecture and roadma Additional Information All your information will be kept confidential according to EEO guidelines. •NO C2C •