Deliver high-impact, client-facing engagements independently and/or lead specific workstreams under the supervision of an engagement lead and principal consultants.
Build and optimize LLM applications, including AI Agents, RAG systems, evaluation pipelines, prompt chaining, and output refinement.
Design, implement, and deploy GenAI pipelines using tools such as DSPy, MLFlow, LangChain, LlamaIndex, and Databricks Mosaic AI.
Work hands-on with models like OpenAI GPT, LLaMA, Claude, and others—fine-tuning or prompt-tuning as required.
Ingest and process unstructured and structured data for use in GenAI systems, including document parsing, chunking, vectorization, and retrieval.
Collaborate with cross-functional teams to build custom UI and API integrations and GenAI-powered user experiences.
Implement enterprise-grade best practices for security, compliance, evaluation, and governance in GenAI projects.
Develop evaluation frameworks using MLFow, Mosaic AI Eval tools, and standard and custom metrics.
Support CI/CD and DABs for AI applications and promote code and model artifacts across environments.
Contribute to internal accelerators and reusable GenAI components as part of our growing framework library.
Work closely with senior leadership to design architecture and delivery plans tailored to client needs.
Requirements
B.S. in Computer Science or equivalent technical field.
3–5 years of experience in Machine Learning or NLP; at least 1–2 years working with LLMs or Generative AI systems, preferably on Databricks.
Proficiency with open-source LLM tooling such as Hugging Face Transformers, LangChain, or similar orchestration libraries.