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# GenAI Engineer

- **Company:** Synechron Inc
- **Location:** Menlo Park, CA, United States
- **Experience:** Experienced
- **Salary:** $105,000.0 - $115,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Unit Testing, Microsoft Azure, Cloud Computing, Cloud Engineering, Software Documentation, Code Review, Computer Programming, Databases, Continuous Integration, Software Debugging, Django Web Framework, Elasticsearch, Monitoring of Systems, JSON, Python (Programming Language), PostgreSQL, Machine Learning, MongoDB, Natural Language Processing, Object-Oriented Software Development, Redis, OpenAI, Tensorflow, Software Safety, Search Technologies, Software Construction, Software Engineering, Unstructured Data, Web Application Frameworks, Pinecone, Google Cloud, Chatbots, Pytorch, LangChain, Retrieval-Augmented Generation, Transfer Learning, Flask (Web Framework), Large Language Models, Prompt Engineering, Google Vertex AI, Model Validation, Software Application Programming, Llamaindex, Generative AI, Backend, Agentic-AI, Git, Fastapi, Scikit Learn, Kubernetes, HuggingFace, Weaviate, Integration Frameworks, Milvus, Machine Learning Operations, FAISS, Claude, Api Design, Google Gemini, Restful APIs, Semantic Kernel, GPT, Software Version Control, Software Library, Docker, ChromaDB
- **Published:** October 31, 2026
- **Apply:** https://www.dice.com/job-detail/6826339e-1713-40b8-92bf-9510a743824d

## About the Role

* 2+ years of professional experience in Python development.
 * Experience building applications using Generative AI or large language models.
 * Strong knowledge of Python programming, object-oriented design, and software development practices.
 * Experience working with REST APIs, JSON, databases, and third-party integrations.
 * Knowledge of prompt engineering and LLM application development.
 * Experience with RAG, embeddings, semantic search, and vector databases.
 * Familiarity with machine learning and natural language processing concepts.
 * Experience with Git, unit testing, debugging, and code documentation.
 * Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

 * Experience with LangChain, LlamaIndex, Semantic Kernel, or similar frameworks.
 * Experience with OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, or Hugging Face.
 * Knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
 * Experience developing APIs with FastAPI, Flask, or Django.
 * Familiarity with Docker, Kubernetes, CI/CD, and MLOps practices.
 * Experience with databases such as PostgreSQL, MongoDB, Elasticsearch, or Redis.
 * Knowledge of machine learning libraries such as PyTorch, TensorFlow, scikit-learn, or Transformers.
 * Understanding of model fine-tuning, LoRA, PEFT, and model evaluation techniques.
 * Experience with AI safety, data privacy, security, and responsible AI practices.
 * Familiarity with observability and monitoring tools for production AI systems.

## Description

We are seeking a talented Generative AI Developer with strong Python experience to design, develop, and deploy AI-powered applications and intelligent automation solutions. The ideal candidate will have hands-on experience with large language models, prompt engineering, Retrieval-Augmented Generation (RAG), machine learning frameworks, and cloud-based AI services.

The successful candidate will work closely with product managers, software engineers, data scientists, and business stakeholders to build scalable, secure, and high-performing Generative AI solutions., * Design and develop Generative AI applications using Python.

 * Build and integrate solutions using large language models such as GPT, Claude, Gemini, Llama, or similar models.
 * Develop prompt templates, prompt chains, and evaluation frameworks to improve model accuracy and reliability.
 * Implement Retrieval-Augmented Generation (RAG) pipelines using enterprise data sources.
 * Work with vector databases such as Pinecone, FAISS, Weaviate, Milvus, or Chroma.
 * Develop AI agents, conversational applications, chatbots, and intelligent automation workflows.
 * Integrate AI models with internal systems, APIs, databases, and third-party platforms.
 * Use frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent tools.
 * Prepare, clean, process, and manage structured and unstructured data.
 * Develop APIs and backend services using Python frameworks such as FastAPI or Flask.
 * Evaluate model performance, response quality, latency, cost, and safety.
 * Implement techniques to reduce hallucinations and improve factual accuracy.
 * Collaborate with engineering teams to deploy AI solutions into production.
 * Apply software engineering best practices, including version control, testing, documentation, and code reviews.
 * Monitor deployed models and applications for reliability, security, and performance.
 * Stay current with developments in Generative AI, machine learning, NLP, and cloud technologies.