Lingaro

Lingaro

Lingaro Group is a leading end-to-end data services partner specializing in Business Intelligence and Data Warehouse solutions. With a focus on digital transformation, Lingaro provides technology-enabled solutions to Fortune 500 enterprises and global ...

IT Services
5K-10K
Founded 2008

Description

  • Lead discovery and solution design for GenAI use cases, translating business problems into architectures involving LLMs, RAG, fine-tuning, agents, and guardrails.
  • Build end-to-end GenAI applications covering data ingestion, retrieval, orchestration, APIs, backends, and user interfaces.
  • Design and implement RAG pipelines using vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks.
  • Select models, develop prompting strategies, and perform fine-tuning with LoRA, QLoRA, and SFT for text, code, and multimodal models.
  • Evaluate solutions through relevance, robustness, and A/B testing methods.
  • Implement safety, compliance, and governance controls, including filters, PII handling, audit logs, and human review.
  • Collaborate with data engineers, product owners, and full-stack developers on scalable architectures, SLAs, and enterprise integrations.
  • Gather technical requirements, estimate work, and conduct targeted proofs of concept for emerging GenAI technologies.
  • Mentor data scientists and engineers and contribute reusable libraries, templates, and components.

Requirements

  • 6+ years of experience in Data Science or AI engineering.
  • 4+ years of experience developing production-ready Python AI code.
  • 2+ years of experience developing production-ready LLM applications, preferably using RAG.
  • Strong knowledge of Generative AI, including LLMs, chatbots, AI agents, and RAG mechanisms.
  • Deep understanding of LLM evaluators, validators, and guardrails.
  • Hands-on experience with LangChain, LlamaIndex, LangGraph, or similar orchestration frameworks.
  • Experience designing or operating MCP servers and clients for LLM agents.
  • Strong Python skills, including packaging, testing, and production-grade data or ML services.
  • Understanding of ML algorithms, frameworks, efficiency metrics, model lifecycles, and AI architectures.
  • Familiarity with Azure, GCP, or AWS AI services; CI/CD, testing, and containerized deployments are preferred.
  • Ability to collaborate across technical and non-technical teams and communicate complex concepts in English.
  • Preferred experience with ML pipelines, Spark or Databricks, Docker or Kubernetes, GitHub Actions, GitLab, Azure DevOps, and agentic AI frameworks.

Interested in this position?

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