Senior network engineer

Company DescriptionOn-Site1yr contract$10950/month Job DescriptionAbout the RoleWe are seeking a Senior Generative AI Engineer to design, build, and deploy production-grade AI applications powered by large language models (LLMs). In this role, you will lead the end-to-end development of Generative AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG) systems, agentic workflows, model evaluation pipelines, and production infrastructure.

You will work cross-functionally with product, finance, data, and business stakeholders to translate real-world business problems into scalable AI systems that deliver measurable value. 

Job Description:

 Design and develop algorithms for generative models using deep learning techniquesDesign and build LLM-powered applications for internal and/or customer-facing use casesDevelop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systemsBuild and optimize AI agents / agentic workflows for task automation, reasoning, and orchestrationIntegrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriateCreate robust evaluation frameworks for response quality, factuality, latency, safety, and reliabilityImplement prompt engineering, structured outputs, tool calling, and model optimization strategiesDeploy scalable AI services to cloud environments using modern software engineering and MLOps practicesBuild monitoring, observability, and feedback loops for model and application performance in productionEstablish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systemsCollaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunitiesMentor other engineers and contribute to architecture, technical direction, and engineering best practices QualificationsRequired QualificationsBachelor's degree in Computer Science, Engineering, Machine Learning, or a related field5+ years of software engineering, machine/deep learning engineering, or applied AI experience2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in productionStrong programming skills in Python and experience with backend/API developmentExperience with LLM application development, including prompt engineering, RAG, tool use, and structured output designExperience in optimizing RAG pipelines using both structured and unstructured dataExperience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalentExperience in generative AI techniques such as GANs, and VAEsHands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI SearchExperience with cloud platforms such as AWS, GCP, or AzureExperience with Docker, Kubernetes, CI/CD, and production deployment practicesStrong understanding of software architecture, scalability, reliability, and distributed systemsExperience building evaluation, testing, and monitoring for AI systemsStrong communication skills and ability to work closely with technical and non-technical stakeholder Preferred QualificationsExperience fine-tuning or adapting open-source LLMsAdvanced knowledge of natural language processing for text generation tasksExperience with PyTorch, TensorFlow, JAX, or related ML frameworksExperience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similarExperience building multi-agent systems or advanced orchestration workflowsExperience with AI safety, guardrails, red-teaming, privacy, and governanceFamiliarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systemsExperience in customer-facing or enterprise SaaS productsExperience in semiconductor/manufacturing, retail and e-commerce sectorsAdditional InformationAll your information will be kept confidential according to EEO guidelines.