Company Description
On-Site
1yr contract
$10950/month
Job Description
About the Role
We 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:
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Design and develop algorithms for generative models using deep learning techniques
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Design and build LLM-powered applications for internal and/or customer-facing use cases
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Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems
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Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration
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Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate
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Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability
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Implement prompt engineering, structured outputs, tool calling, and model optimization strategies
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Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices
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Build monitoring, observability, and feedback loops for model and application performance in production
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Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems
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Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities
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Mentor other engineers and contribute to architecture, technical direction, and engineering best practices
Qualifications
Required Qualifications
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Bachelor’s degree in Computer Science, Engineering, Machine Learning, or a related field
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5+ years of software engineering, machine/deep learning engineering, or applied AI experience
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2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production
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Strong programming skills in Python and experience with backend/API development
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Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design
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Experience in optimizing RAG pipelines using both structured and unstructured data
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Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent
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Experience in generative AI techniques such as GANs, and VAEs
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Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search
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Experience with cloud platforms such as AWS, GCP, or Azure
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Experience with Docker, Kubernetes, CI/CD, and production deployment practices
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Strong understanding of software architecture, scalability, reliability, and distributed systems
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Experience building evaluation, testing, and monitoring for AI systems
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Strong communication skills and ability to work closely with technical and non-technical stakeholder
Preferred Qualifications
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Experience fine-tuning or adapting open-source LLMs
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Advanced knowledge of natural language processing for text generation tasks
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Experience with PyTorch, TensorFlow, JAX, or related ML frameworks
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Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar
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Experience building multi-agent systems or advanced orchestration workflows
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Experience with AI safety, guardrails, red-teaming, privacy, and governance
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Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems
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Experience in customer-facing or enterprise SaaS products
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Experience in semiconductor/manufacturing, retail and e-commerce sectors
Additional Information
All your information will be kept confidential according to EEO guidelines.