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About the Role
Docusign's Digital Technology Services team 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. This hands-on role requires deep expertise in software design, distributed systems, APIs, and AI-enabled architectures to develop and operate custom applications, AI agents, middleware services, and integration frameworks. A key aspect is applying agentic AI patterns to enhance system intelligence, resilience, and developer productivity.
Responsibilities
- Conduct applied AI research to translate theoretical GenAI advancements into production-ready software features.
- Lead Technical Feasibility Studies and rapid prototyping to provide the engineering foundation for "build vs. buy" architectural decisions.
- Engineer Production-Grade NLP algorithms and information retrieval systems using SpaCy, NLTK, and Hugging Face.
- Design, build, and maintain scalable RAG architectures that connect foundational Large Language Models (LLMs) to proprietary enterprise databases.
- Evaluate and apply appropriate embedding models, vector databases, and LLMs based on cost, latency, security, and performance requirements.
- Build enterprise-grade conversational interfaces and analytical AI tools (QueryGPT) that interface directly with structured data systems via custom middleware.
- Design and Build autonomous multi-agent frameworks (e.g., CrewAl, LangGraph) and scalable agentic platforms, focusing on distributed system architecture and secure execution environments.
- Develop Custom Extensions and API-based integrations for LLM models, creating sophisticated AI assistants through backend systems programming.
- Execute Model Engineering through supervised fine-tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) to optimize model weight distribution for scalability and reliability.
- Develop algorithmic prompt-chaining logic and maintain a centralized, version-controlled prompt library integrated into the CI/CD pipeline.
- Architect and Develop end-to-end evaluation pipelines for LLMs/SLMs, Engineering complex telemetry to capture performance, quantization efficiency, and fine-tuning convergence metrics.
- Own the technical documentation, code maintainability, and reproducibility of the AI infrastructure, ensuring alignment with engineering excellence standards.
- Bridge time zones effectively; ensure crisp handoffs and decision velocity with US counterparts.
Requirements
- Bachelor's or Master's degree in Computer Science or a related field.
- 6+ years of relevant experience with a Master's degree, or 8+ years with a 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 (e.g., 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 large language models (LLMs).
- Experience in natural language processing (NLP), prompt engineering, instruction tuning, context window optimization, advanced tokenization strategies, and leveraging pre-trained LLMs (via APIs or open-source models).
- Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, and agentic/multi-agent orchestration tools like LangGraph, CrewAl, or similar.
- Experience developing and implementing an interactive search platform Glean.
- Experience with programming languages such as Python and Bash, as well as frameworks/tools like React and Streamlit.
- Experience with any copilot tools for coding such as Github copilot or Cursor.
- Experience with vector databases such as FAISS, Pinecone, Weaviate, and Chroma for embedding storage and retrieval.
- Experience with data preprocessing, augmentation, and visualization techniques.
- Experience contributing to GenAI projects from ideation through deployment, iteration, and evaluation of LLM performance.
- Experience working with containerization and orchestration technologies like Docker, Kubernetes, and AWS ECS.
- Experience with key AWS services including VPC, IAM, MWAA (Managed Workflows for Apache Airflow), and ECS.
- Experience with software development best practices including Git, testing, CI/CD pipelines, infrastructure as code (Terraform), automation, and MLOps for GenAI.
- 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 the ability to think creatively.
- 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.
- This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming.
Skills
- Agentic AI systems
- Complex integrations
- Software design
- Distributed systems
- APIs
- AI-enabled architectures
- Custom-built applications
- AI agents
- Middleware services
- Integration frameworks
- Orchestration
- Tool-using agents
- Retrieval-Augmented Generation (RAG)
- Workflow automation
- NLP
- SpaCy
- NLTK
- Hugging Face
- Large Language Models (LLMs)
- Embedding models
- Vector databases
- Conversational interfaces
- Analytical AI tools
- QueryGPT
- Multi-agent frameworks
- CrewAl
- LangGraph
- LLM models
- Backend systems programming
- Model Engineering
- Supervised fine-tuning (SFT)
- Reinforcement Learning from Human Feedback (RLHF)
- Prompt-chaining logic
- Prompt library
- CI/CD pipeline
- LLM evaluation pipelines
- Telemetry
- Quantization efficiency
- Fine-tuning convergence metrics
- Technical documentation
- Code maintainability
- Reproducibility
- AI infrastructure
- Python
- Bash
- React
- Streamlit
- Github copilot
- Cursor
- FAISS
- Pinecone
- Weaviate
- Chroma
- Data preprocessing
- Data augmentation
- Data visualization
- Containerization
- Docker
- Kubernetes
- AWS ECS
- AWS VPC
- AWS IAM
- AWS MWAA
- Git
- Testing
- Infrastructure as code (Terraform)
- Automation
- MLOps for GenAI
- Cloud platforms
- AWS
- Azure
Location
- Hybrid
Work Type
- Hybrid
- Full-time
Experience Level
- Senior
- 6+ years of relevant experience with a Master's degree
- 8+ years with a Bachelor's degree
Education Level
- Bachelor's degree
- Master's degree
Salary/Compensations
- California: $164,700.00 - $266,000.00 base salary
- Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
- Stock: This role is eligible to receive Restricted Stock Units (RSUs).
Benefits
- Paid Time Off: earned time off, as well as paid company holidays based on region
- Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
- Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
- Retirement Plans: select retirement and pension programs with potential for employer contributions
- Learning and Development: options for coaching, online courses and education reimbursements
- Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events
About the Company
- Docusign brings agreements to life.
- Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives.
- With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents.
- Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM).
Equal Opportunity
- Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work.
- We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life.
- Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures.
- Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach.
- We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category.