GenAI-Engineer
Fractal Analytics16 hours ago
Mumbai, India or Bengaluru, IndiaSenior
Responsibilities
- Design, develop, and implement advanced solutions leveraging large language models and Generative AI.
- Build, train, and fine-tune machine learning and large language models, including production-grade LLM applications.
- Design scalable APIs, pipelines, orchestration layers, RAG pipelines, agentic workflows, and hybrid systems.
- Build reusable code libraries, frameworks, accelerators, templates, tools, and reference architectures.
- Develop evaluation frameworks, guardrails, fallback strategies, and responsible AI controls for robust LLM systems.
- Optimize AI systems across latency, cost, accuracy, reliability, maintainability, and adoption.
- Translate ambiguous business problems into structured AI approaches, measurable outcomes, and solution success metrics.
- Engage with business and technical stakeholders, clients, and cross-functional teams on requirements, solution presentations, proofs of concept, proposals, and decision-making.
- Contribute across the software development lifecycle, including design, implementation, testing, deployment, maintenance, code reviews, and design reviews.
- Influence technical roadmaps, integrate contributions into core systems, mentor junior team members, and promote quality standards.
- Create internal intellectual property and contribute to knowledge sharing, training, and capability building.
- Evaluate new Generative AI advancements and determine when alternative approaches should be used instead of LLMs.
Requirements
- 5–8 years of experience as a Data Scientist.
- Deep expertise in Generative AI, NLP, and LLM technologies.
- Hands-on experience with machine learning model building and training or fine-tuning large language models from the ground up.
- Strong technical background in machine learning, deep learning, and modern AI frameworks.
- Experience with LangChain, LlamaIndex, vector databases, prompt engineering, Azure OpenAI function calling, and multimodal models.
- Experience with Azure OpenAI and other open-source or SaaS LLMs, including Claude and GPT models.
- Experience with at least one agentic Generative AI framework, such as CrewAI, AutoGen, LangGraph, n8n, LangFlow, SmolAgents, or Semantic Kernel.
- Advanced RAG experience, including hybrid retrieval, knowledge graph-based retrieval, multi-hop RAG, hierarchical or contextual retrieval, and RAG pipeline evaluation and monitoring.
- Knowledge of classical NLP applications including text classification, topic modeling, question-answering systems, conversational AI, search, Document AI, summarization, content generation, and named entity recognition.
- Experience with the Databricks ecosystem, including Databricks Genie and Databricks AI/BI.
- Knowledge of Microsoft Copilot Studio and no-code or low-code application development.
- Experience with MCP servers, tools, skills, and the creation and maintenance of reusable components.
- Strong analytical, problem-solving, communication, architecture, stakeholder engagement, and solution trade-off skills.
- Experience contributing to code reviews, design reviews, mentorship, internal knowledge sharing, and capability building.
Tech Stack
Databricks
Categories
About Fractal Analytics
Fractal builds enterprise AI and analytics solutions—delivered as consulting services and software products—for large global enterprises, especially Fortune 500 firms. Its teams embed AI in decisions across marketing, pricing, supply chain, forecasting, and customer experience. Founded in 2000 and headquartered in New York, Fractal is publicly listed and operates across North America, EMEA, and APAC.