What are the responsibilities and job description for the Senior Consultant – Enterprise AI (GenAI / LLM) position at DynPro Inc.?
Role Overview
We are looking for a Senior Consultant with a strong Data Science / AI background to design and deliver end-to-end enterprise AI solutions. The ideal candidate will have hands-on experience with GenAI, LLMs, and RAG, and a proven ability to translate business problems into scalable AI-driven solutions.
This role is solution-focused, not platform-heavy — we are specifically looking for candidates who have owned AI use cases from problem definition to production delivery.
Key Responsibilities
- Design and deliver end-to-end AI solutions for enterprise use cases across HR, IT, Finance, Operations, and Customer Support.
- Build AI copilots, chatbots, and knowledge assistants using LLMs and enterprise data.
- Develop and optimize RAG (Retrieval-Augmented Generation) pipelines for intelligent search and automation.
- Work with structured and unstructured data to enable decision-making and self-service capabilities.
- Apply LLMs, prompt engineering, and agentic workflows to solve business problems.
- Collaborate with business stakeholders to gather requirements and translate them into AI solutions.
- Ensure solutions meet enterprise standards for security, governance, and compliance.
- Implement best practices for LLMOps, evaluation, monitoring, and guardrails.
- Track solution performance, user adoption, and business impact.
- Support deployment, iteration, and continuous improvement of AI systems.
Required Qualifications
- 7–10 years of experience in Data Science, AI/ML, or AI Consulting roles.
- Hands-on experience building GenAI / LLM-based applications in enterprise environments.
- Proven experience designing and delivering end-to-end AI solutions (not just components).
- Strong experience with RAG pipelines, enterprise search, and knowledge retrieval systems.
- Proficiency in Python for data analysis and AI workflows.
- Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar.
- Experience with vector databases/search tools (Pinecone, FAISS, Chroma, OpenSearch, Azure AI Search, etc.).
- Experience with cloud AI platforms such as Azure OpenAI, AWS Bedrock, or Vertex AI.
- Strong understanding of LLMOps, evaluation frameworks, monitoring, and prompt/version management.
- Ability to work closely with business stakeholders and drive AI use cases end-to-end.
Preferred Qualifications
- Experience building enterprise AI copilots or internal automation tools.
- Familiarity with agentic AI, tool/function calling, MCP, or orchestration frameworks.
- Experience integrating AI solutions with enterprise platforms like ServiceNow, Workday, Microsoft 365, SharePoint, Teams, Slack, Salesforce, etc.
- Experience in consulting environments or client-facing roles.
- Exposure to workflow automation tools (Power Automate, UiPath, etc.).
Ideal Candidate Profile
- Strong Data Scientist / AI Consultant background
- Has built real GenAI solutions using enterprise data
- Comfortable with business interaction and solution ownership
- Not purely backend, platform, or infrastructure-focused
Regards,
Gaganpreet Singh
Lead - Talent Acquisition
www.dynpro.com