> Markdown version of [/jobs/ext/2152026-genai-architect-developer](https://www.wearedevelopers.com/jobs/ext/2152026-genai-architect-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GenAI Architect/Developer - **Company:** BCforward - **Location:** Richmond, VA, United States - **Experience:** Expert - **Salary:** $146,078.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Amazon Web Services, Data Analysis, Application Integration Architecture, Artificial Neural Networks, Microsoft Azure, Cloud Computing, Elasticsearch, Python (Programming Language), Logistic Regression, Machine Learning, Language Modeling, NLTK (NLP Analysis), NumPy, Open Source Technology, Performance Tuning, Azure Machine Learning, Search Technologies, SQL Databases, Support Vector Machine, Google Cloud, Feature Engineering, Pytorch, Flask (Web Framework), Large Language Models, Random Forest, Prompt Engineering, Deep Learning, Topic Modeling, Naive Bayes, Generative AI, Fastapi, Pandas, Heroku, Scikit Learn, HuggingFace, Machine Learning Operations, Virtual Agents, Streamlit Framework, GPT - **Published:** August 20, 2026 - **Apply:** https://www.dice.com/job-detail/b0c52d9c-c9c6-43ed-a993-3cb78b7c672c ## About the Role We are seeking a Senior Architect to join our dynamic team on the ENACT Modernization project. The ideal candidate will have strong experience in Python, Azure ML, Generative AI, and data science and a proven ability to design, develop, and deploy GenAI solutions end to end., * Proven hands-on experience implementing GenAI projects using open-source LLMs (Llama, GPT OSS, Gemma, Mistral) and proprietary APIs (OpenAI, Anthropic). * Experience fine-tuning models such as LLaMA2 and GPT-4 with custom datasets for varied tasks. * Expertise in prompt engineering for GPT-4, GPT-3, LLaMA2, and Gemini Pro. * Strong Python development skills, including Pandas and NumPy for data analysis and feature engineering. * Strong background in Retrieval Augmented Generation implementations and vector search. * Expertise in machine learning models such as SVM, Logistic Regression, Random Forest, Naive Bayes, and Neural Networks. * Extensive NLP experience: embeddings (Word2Vec, GloVe, FastText, Universal Sentence Encoder, contextual embeddings), topic modeling (LSA), and search (FAISS, Elasticsearch). * Deep learning for NLP with libraries such as PyTorch and Hugging Face. * Proficiency with Scikit-learn, Pandas, NumPy, NetworkX, and NLTK. * Experience deploying ML models to Streamlit, Hugging Face Spaces, or Heroku. * Experience building and integrating APIs using REST, FastAPI, or Flask to serve models. * Knowledge of agentic AI frameworks and orchestration patterns. * Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform, with preference for Azure ML. * Experience working in Agile environments with strong problem-solving and communication skills. Preferred Skills: * Fine-tuning and optimization of open-source LLMs or small language models. * Experience with discourse semantics, anaphora resolution, DRT/DRS, and tools such as Boxer, Neural DRS, or JAMR. * Experience with SQL and related data tools. * Familiarity with Horizon toolset and change management practices. ## Description * Architect and develop GenAI solutions leveraging open-source and proprietary LLMs. * Design and implement fine-tuning and prompt engineering strategies for LLMs. * Build Retrieval Augmented Generation pipelines and scalable NLP services. * Develop APIs and deploy ML models to cloud and application platforms. ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Vectorize all the things! 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