GenAI Developer

Location: Bengaluru, India

Department: Engineering

Work Mode: Hybrid

About the Role

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 business processes and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data trapped inside documents, connecting it to systems of record. As the #1 company in e-signature and contract lifecycle management (CLM), we’re seeking a skilled Generative AI Developer to join our dynamic Engineering team and solve critical enterprise problems through cutting-edge AI innovation. In this individual contributor role reporting to the Senior Director, you’ll design, develop, and deploy generative AI applications that improve employee and developer productivity while driving business growth. You’ll build autonomous agents, implement world-class Glean platforms, and create RAG pipelines that power intelligent agreement analytics and e-signature workflows. Your work will directly contribute to highly demanding AI initiatives, integrating GenAI with Docusign’s core platforms to deliver secure, scalable solutions with a strong emphasis on governance and performance optimization. This role is perfect for a determined problem-solver eager to learn and comfortable with ambiguity in a fast-paced innovation culture. You’ll design evaluation pipelines for LLMs, develop advanced NLP algorithms, fine-tune models for enterprise reliability, and collaborate across Product, Design, ML, and Data Engineering teams to translate business requirements into technical excellence. Working with modern frameworks like LangChain, CrewAI, and vector databases, you’ll enable conversational AI tools like QueryGPT and custom agents that transform how Docusign employees interact with agreement data. This hybrid role (minimum 2 days/week in-office) offers the opportunity to make a real impact on our company’s AI strategy and be part of a team committed to engineering excellence, automation, and documentation. At Docusign, everything is equal. We ensure every team member has equal opportunity to succeed, exchange ideas openly, build lasting relationships, and do the work of their life. Join us to feel deep pride in work that makes the world more agreeable, supported by competitive compensation, comprehensive benefits, and a culture of trust and innovation.

Key Responsibilities

• Design and implement evaluation pipelines for closed and open-source LLMs, capturing metrics like performance, latency, cost, hallucination, helpfulness, and harmlessness
• Develop advanced Textual Information Retrieval, classification, and clustering algorithms using SpaCy, NLTK, and Hugging Face
• Enable GenAI business use cases on Docusign infrastructure with strong emphasis on security, governance, and intelligent agreement management integration
• Build autonomous and workflow-based agents for business applications using CrewAI or similar frameworks to accelerate e-signature and CLM workflows
• Drive world-class implementation of the no-code agentic platform Glean, developing custom agents as AI assistants for Docusign employees
• Fine-tune GenAI models to optimize performance, scalability, and reliability for enterprise-grade agreement processing
• Implement prompt engineering best practices and contribute to centralized prompt library to minimize token usage and improve accuracy
• Develop robust RAG pipeline automation tools integrating diverse datasets, vector databases, and knowledge graphs for agreement analytics
• Build conversational tools (QueryGPT, analytical AI) to answer business questions from structured data systems and enterprise ChatGPT applications
• Conduct research to advance generative AI capabilities and apply findings to real-world Docusign use cases
• Collaborate with business teams to translate requirements into effective GenAI technical solutions
• Document processes, models, and code to ensure maintainability, reproducibility, and engineering excellence

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field
• 3+ years of relevant experience with a Master’s degree, or 5+ years with a Bachelor’s degree
• Proven experience developing and deploying GenAI-powered applications such as intelligent chatbots, AI copilots, and autonomous agents
• Strong understanding of Large Language Models (LLMs), transformer architectures (BERT, GPT, T5), RAG, embedding techniques, knowledge graphs, and LLM fine-tuning/training
• Direct working experience developing and implementing the interactive search platform Glean
• Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Chroma) and LLM orchestration frameworks (LangChain, LlamaIndex, LangGraph, CrewAI)
• Proficiency in Python, Bash, React, Streamlit, and AWS services (VPC, IAM, MWAA, ECS)
• Experience with containerization (Docker, Kubernetes) and MLOps best practices including CI/CD, Git, and Terraform

Preferred Qualifications

• One or more certifications such as AWS Cloud, Solution Architect, Technical Architect, or GenAI-related certifications
• Proficiency in additional cloud platforms such as Azure
• 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
• Experience with copilot tools for coding such as GitHub Copilot or Cursor
• Strong commitment to engineering excellence through automation, innovation, and documentation

Required Skills

• Large Language Models (LLMs) and transformer architectures
• Retrieval-Augmented Generation (RAG) and embedding techniques
• LLM orchestration frameworks (LangChain, LlamaIndex, CrewAI, LangGraph)
• Vector databases (FAISS, Pinecone, Weaviate, Chroma)
• Glean interactive search platform implementation
• Python, Bash, React, and Streamlit development
• AWS services (VPC, IAM, MWAA, ECS) and cloud infrastructure
• Docker, Kubernetes, and container orchestration
• Prompt engineering and instruction tuning
• MLOps, CI/CD pipelines, Git, and Terraform
• Natural Language Processing (NLP) with SpaCy, NLTK, Hugging Face
• Data preprocessing, augmentation, and visualization
• Strong problem-solving and creative thinking
• Cross-functional collaboration and communication
• Security and governance best practices
• Model evaluation and optimization (quantization, fine-tuning)

Benefits

• Competitive salary and equity package with top-tier technology company
• Comprehensive health, dental, and vision insurance coverage
• 401(k) matching and employee stock purchase program
• Flexible time off policy including unlimited PTO and paid family leave
• Professional development stipend and conference attendance budget
• Hybrid work model with modern office spaces in prime locations
• Wellness programs including mental health support and fitness reimbursement
• Volunteer time off and charitable donation matching
• Parental leave and fertility assistance benefits

DocuSign is an Equal Opportunity Employer.