Lovelytics Principal Consultant, GenAI to lead end-to-end delivery of Generative AI and Agentic AI solutions on Databricks. Provide technical leadership and client advisory in AI architecture and deployment.
Responsibilities
Lead end-to-end delivery of smaller GenAI and Agentic AI solutions on Databricks, through production deployment
Own client engagements including key technical decisions across agents, LLMs, Compound AI, evaluation, governance, observability, and integration patterns
Lead technical workstreams and provide day-to-day technical direction to Senior/Lead Engineers and Consultants
Serve as a trusted technical advisor to client stakeholders, translating business requirements into pragmatic AI solutions and clearly communicating architecture and tradeoffs
Ensure solutions meet high standards for quality, scalability
Qualification
Experience with GenAI evaluationWorking knowledge of classical MLStrong client-facing consulting
Required
Strong hands-on experience building and deploying production GenAI solutions, including LLM applications, AI agents, tool calling, orchestration, and Compound AI systems.
Strong Databricks experience across relevant capabilities such as Mosaic AI, Model Serving, MLflow, Unity Catalog, Vector Search, Databricks Apps, and Lakehouse architecture.
Strong Python and software engineering skills, including APIs, testing, CI/CD, deployment, and integration patterns.
Experience with GenAI evaluation, prompt engineering/optimization, guardrails, monitoring, observability, and LLMOps.
Working knowledge of classical ML, data engineering, and analytics and how they integrate with GenAI solutions.
Strong client-facing consulting, communication, and presentation skills.
Strong problem-solving skills and ability to operate effectively when requirements are ambiguous or evolving.
Demonstrated technical leadership and ability to mentor and guide Senior/Lead resources.
Ability to explain complex technical concepts clearly to both technical and business stakeholders.
Our Ideal Candidate's Skills and Experiences:
B.S. in Computer Science or equivalent technical field.
5+ years in Data Analytics with significant experience in data, ML, AI, cloud, or software engineering.