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Salary: USD 164,700 - 266,000 / annual
DocuSign is seeking a Senior Software Engineer to design, build, and scale intelligent, enterprise-grade software solutions with a strong focus on agentic AI systems and complex integrations across application engineering platforms. This is a hands-on individual contributor role reporting to the Director of Application Support and Operations.
You will develop and operate custom-built applications, AI agents, middleware services, and integration frameworks that connect core technology platforms with enterprise and external systems. Key responsibilities include:
• Conducting applied AI research to translate theoretical GenAI advancements into production-ready software features
• Leading technical feasibility studies and rapid prototyping for "build vs. buy" architectural decisions
• Engineering production-grade NLP algorithms and information retrieval systems using SpaCy, NLTK, and Hugging Face
• Designing, building, and maintaining scalable RAG (Retrieval-Augmented Generation) architectures that connect foundational LLMs to proprietary enterprise databases
• Evaluating and applying appropriate embedding models, vector databases, and LLMs based on cost, latency, security, and performance requirements
• Building enterprise-grade conversational interfaces and analytical AI tools that interface with structured data systems via custom middleware
• Designing and building autonomous multi-agent frameworks (e.g., CrewAI, LangGraph) and scalable agentic platforms
• Developing custom extensions and API-based integrations for LLM models
• Executing model engineering through supervised fine-tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF)
• Developing algorithmic prompt-chaining logic and maintaining a centralized, version-controlled prompt library integrated into CI/CD pipelines
• Architecting and developing end-to-end evaluation pipelines for LLMs/SLMs with complex telemetry
• Owning technical documentation, code maintainability, and reproducibility of AI infrastructure
• Bridging time zones effectively with US counterparts
The role is hybrid with a minimum 2 days per week in-office expectation at the San Francisco location.
REQUIREMENTS:
• Bachelor's or Master's degree in Computer Science or related field
• 6+ years of relevant experience (with Master's degree) OR 8+ years (with Bachelor's degree)
• Experience developing and deploying GenAI-powered applications such as intelligent chatbots, AI copilots, and autonomous agents
• Experience with Large Language Models (LLMs), transformer architectures (BERT, GPT, T5), and their applications in text generation, summarization, question answering, and code synthesis
• Experience with Retrieval-Augmented Generation (RAG), embedding techniques, knowledge graphs, and fine-tuning/training of LLMs
• Experience in natural language processing (NLP), prompt engineering, instruction tuning, context window optimization, advanced tokenization strategies, and leveraging pre-trained LLMs
• Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, and agentic/multi-agent orchestration tools like LangGraph, CrewAI, or similar
• Experience developing and implementing an interactive search platform (Glean experience noted)
• Proficiency with programming languages such as Python and Bash, and frameworks/tools like React and Streamlit
• Experience with copilot tools for coding such as GitHub Copilot or Cursor
• Experience with vector databases such as FAISS, Pinecone, Weaviate, and Chroma
• Experience with data preprocessing, augmentation, and visualization techniques
• Experience contributing to GenAI projects from ideation through deployment, iteration, and evaluation
• Experience with containerization and orchestration technologies like Docker, Kubernetes, and AWS ECS
• Experience with key AWS services including VPC, IAM, MWAA, and ECS
• Experience with software development best practices including Git, testing, CI/CD pipelines, infrastructure as code (Terraform), automation, and MLOps for GenAI
PREFERRED:
• Strong commitment to engineering excellence through automation, innovation, and documentation
• One or more certifications such as Cloud, Solution Architect, Technical Architect, or GenAI-related certifications
• Proficiency in cloud platforms such as AWS and Azure
• Strong problem-solving skills and creative thinking
• Strong collaboration skills in cross-functional teams (Product, Design, ML, Data Engineering)
• Ability to explain complex GenAI concepts to both technical and non-technical stakeholders
