Who you are

• Our ideal candidate blends technical depth with consulting acumen and thrives in a collaborative, fast-paced environment
• 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
• Strong hands-on experience with Databricks (Unity Catalog, MLFlow, Delta Tables, etc.)
• Familiarity with GenAI-specific challenges including hallucination mitigation, grounding techniques, and evaluation frameworks
• Experience designing and deploying applications with security, compliance, and scalability in mind
• Excellent communication skills and a strong ability to engage with technical and business stakeholders

What the job involves

• Lovelytics is seeking a Generative AI Engineer (Senior Consultant) with hands-on experience delivering client-facing projects in the Generative AI domain, particularly on the Databricks platform
• As part of our growing AI & GenAI practice, this role offers an exciting opportunity to design and deploy state-of-the-art solutions that combine language models, vector databases, and cutting-edge orchestration frameworks
• The Sr Consultant will play a pivotal role in delivering client engagements focused on AI Agents, Retrieval-Augmented Generation (RAG), LLM application development, prompt engineering / DSPy, GenAI-driven automation, and advanced NLP
• 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