Sr. Gen AI Engineer

• 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

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

   

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

 *** NO C2C ***