Lingaro

Senior Full Stack Data Scientist

Lingaro

full-time

Posted on:

Location Type: Remote

Location: India

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Job Level

Senior

Tech Stack

AWSAzureCloudGoogle Cloud PlatformPython

About the role

  • Lead discovery and solution design for GenAI use cases, translating business problems into concrete architectures (LLM decision, RAGs, fine‑tuning, agents, guardrails)
  • Build end‑to‑end GenAI applications: data ingestion, retrieval layer, orchestration (e.g. LangChain/LlamaIndex/LangGraph), API/backend, and simple UI where needed.
  • Design and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness.
  • Perform model selection, prompting strategies, and fine‑tuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including evaluation and A/B testing.
  • Implement safety, compliance, and governance controls (input/output filters, PII handling, audit logs, human‑in‑the‑loop review where required).
  • Collaborate with data engineers, product owners, and full‑stack developers on scalable architectures, SLAs, and integration with existing enterprise systems
  • Gather technical requirements and estimate planned work.
  • Mentor other data scientists/engineers in GenAI patterns, code quality, and best practices; contribute to internal libraries, templates, and reusable components.
  • Stay current with GenAI landscape (new open and hosted models, agentic frameworks, evaluation techniques) and perform targeted PoCs to validate them.

Requirements

  • 6+ years of experience in Data Science/AI engineering
  • At least 4+ years of experience in production-ready Python AI-related code development.
  • At least 2+ years of experience in production-ready LLM-related code development, preferably based on the Retrieval-Augmented Generation (RAG) concept.
  • Strong analytical and problem-solving skills with the ability to optimize AI solutions for diverse applications.
  • Strong knowledge and experience in Generative AI, including LLMs, chatbots, AI agents, and RAG mechanisms.
  • Deep understanding of LLM evaluators, validators, and guardrails.
  • Hands‑on experience with one or more GenAI frameworks: LangChain, LlamaIndex, LangGraph, or similar orchestration stacks.
  • Hands-on experience designing or operating MCP servers/clients for LLM agents
  • Strong Python skills, including production grade code, packaging, and testing for data/ML services
  • Solid understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model lifecycle, AI architectures.
  • Proven ability to collaborate effectively across technical and non-technical teams.
  • Familiarity with cloud environments such as Azure (preferred), GCP, or AWS, including AI-related managed services.
  • Familiarity with CI/CD, testing, and containerized deployments.
  • Excellent communication skills in English, with the ability to convey complex technical concepts to various audiences.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
PythonGenerative AILLMsRAGLangChainLlamaIndexLangGraphMCP servers/clientsmachine learning frameworksmodel lifecycle
Soft Skills
analytical skillsproblem-solving skillscollaborationmentoringcommunication skills