GenAI Engineer

Bangalore, Karnataka
Permanent
Full-time

9 days ago

Job Description:Company OverviewDocusign 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. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. 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).What you'll doWe are seeking a skilled Generative AI Engineer to join our dynamic team who is eager to solve enterprise problems with GenAI. We are embarking upon many critical AI initiatives to help improve employee productivity, developer productivity, and improve business growth. You will be directly involved in innovating and contributing to these highly demanding AI initiatives. You will be responsible for designing, developing, and deploying generative AI applications to solve complex enterprise problems. You are eager to learn, determined to adapt quickly, and comfortable with some ambiguity in requirement.This position is an individual contributor role reporting to the Senior Director, GenAI.Responsibility

Design and implement evaluation pipelines for both closed and open-source Large and Small Language Models, capturing key metrics such as performance, latency, cost, hallucination, helpfulness, harmlessness, quantization, and fine-tuning
Develop advanced Textual Information Retrieval, classification, and clustering algorithms using frameworks like SpaCy, NLTK, and Hugging Face
Enable GenAI business use cases on Docusign infrastructure with a strong emphasis on security and governance
Build autonomous and workflow-based agents for business applications using CrewAI or similar agentic frameworks, and support agentic AI platforms
Drive world-class implementation of the no-code agentic platform Glean, developing custom agents to serve as AI assistants for employees
Fine-tune GenAI models to optimize performance, scalability, and reliability
Support buy vs. build evaluations for GenAI solutions
Implement prompt engineering best practices to minimize token usage and improve output accuracy; contribute to a centralized prompt library
Develop robust tools to automate RAG pipeline creation, integrating diverse datasets into vector databases and incorporating knowledge graphs as needed
Help building conversational tools to answer business questions from structured data systems ( analytical AI or QueryGPT) and applications like ChatGPT for the enterprise
Conduct research to advance generative AI and apply findings to real-world use cases
Document processes, models, and code to ensure maintainability and reproducibility
Collaborate with business teams to translate requirements into effective technical solutions

Job DesignationHybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law.What you bringBasic

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 in developing and deploying GenAI-powered applications such as intelligent chatbots, AI copilots, and autonomous agents
Strong understanding of Large Language Models (LLMs), transformer architectures (e.g., BERT, GPT, T5), and their applications in text generation, summarization, question answering, and code synthesis
Strong understanding of 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)
Proficiency with LLM orchestration frameworks such as LangChain, LlamaIndex, and agentic/multi-agent orchestration tools like LangGraph, CrewAI, or similar
Direct working experience in developing and implementing an interactive search platform Glean
Proficiency in 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
Hands-on experience with vector databases such as FAISS, Pinecone, Weaviate, and Chroma for embedding storage and retrieval
Familiarity with data preprocessing, augmentation, and visualization techniques
Proven track record of 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
Hands-on expertise with key AWS services including VPC, IAM, MWAA (Managed Workflows for Apache Airflow), and ECS
Familiarity 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 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

Life at DocusignWorking hereDocusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal.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. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live.AccommodationDocusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at .If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at for assistance.#LI-Hybrid #LI-SA4

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