2 months ago
Base Salary
$165k - $266k/yr
Responsibilities
- Conduct applied AI research and translate GenAI advancements into production-ready software features.
- Lead technical feasibility studies and rapid prototypes supporting build-versus-buy architectural decisions.
- Engineer production-grade NLP algorithms and information retrieval systems using spaCy, NLTK, and Hugging Face.
- Design and maintain scalable RAG architectures connecting LLMs to proprietary enterprise databases.
- Evaluate embedding models, vector databases, and LLMs based on cost, latency, security, and performance.
- Build conversational interfaces and analytical AI tools that connect structured data systems through custom middleware.
- Design autonomous multi-agent frameworks and scalable agentic platforms with secure execution environments.
- Develop API-based LLM extensions, AI assistants, and backend integrations.
- Perform supervised fine-tuning and RLHF to improve model scalability and reliability.
- Develop prompt-chaining logic and maintain a version-controlled prompt library integrated with CI/CD.
- Build end-to-end LLM and SLM evaluation pipelines with telemetry for performance, quantization efficiency, and fine-tuning convergence.
- Own technical documentation, code maintainability, reproducibility, and cross-time-zone engineering handoffs.
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 chatbots, copilots, and autonomous agents.
- Experience with LLMs, transformer architectures such as BERT, GPT, and T5, and text generation, summarization, question answering, and code synthesis.
- Experience with RAG, embeddings, knowledge graphs, and fine-tuning or training LLMs.
- Experience with NLP, prompt engineering, instruction tuning, context-window optimization, tokenization, and pretrained LLM APIs or open-source models.
- Experience with LangChain, LlamaIndex, LangGraph, CrewAI, or similar orchestration tools.
- Experience developing and implementing the Glean interactive search platform.
- Experience with Python, Bash, React, and Streamlit.
- Experience using coding copilots such as GitHub Copilot or Cursor.
- Experience with vector databases including FAISS, Pinecone, Weaviate, and Chroma.
- Experience with data preprocessing, augmentation, and visualization.
- Experience contributing to GenAI projects from ideation through deployment, iteration, and evaluation.
- Experience with Docker, Kubernetes, and AWS ECS.
- Experience with AWS VPC, IAM, MWAA, and ECS.
- Experience with Git, testing, CI/CD pipelines, Terraform, automation, and GenAI MLOps.
- Preferred qualifications include cloud, solution architect, technical architect, or GenAI certifications; AWS and Azure proficiency; and strong collaboration, communication, problem-solving, and documentation skills.
Benefits
- Hybrid work arrangement requiring a minimum of two days per week in the office, with weekly in-office expectations; office access is required.
- Company bonus plan for non-sales employees, calculated based on eligible wages and company performance.
- Eligibility for Restricted Stock Units.
- Paid time off and regional company holidays.
- Up to six months of paid parental leave after birth, adoption, or foster placement.
- Health benefit plans, including options with 100% employer-paid coverage and minimum employee contributions from day one.
- Retirement and pension programs with potential employer contributions.
- Coaching, online courses, and education reimbursement options.
- Paid compassionate care leave.
- This position is not eligible for employment in Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia, or Wyoming.
Categories
About DocuSign
DocuSign builds e-signature, contract lifecycle management, and agreement workflow software used by businesses to prepare, sign, and manage contracts. It sells cloud-based subscriptions and APIs that integrate with systems like Salesforce, Microsoft, and Google to automate document workflows and compliance. Founded in 2003 and headquartered in San Francisco, DocuSign is a public company on NASDAQ with over 1.5 million customers in more than 180 countries.