LLM Data Scientist

Greytip Software Private Limited; Hinoba-an; On-site; PHP 360,000 - 720,000; Full time

Job summary

Giniminds seeks a skilled LLM Data Scientist to design, develop, and optimize agentic AI systems and enterprise AI platforms. You will implement LangChain, LangGraph, and LLM flows, build multi-agent workflows, and collaborate with product, engineering, and AIOps teams to deploy production-grade AI capabilities.

The role requires 2+ years in data science and NLP, strong Python and cloud experience, and a hands-on approach to vector databases, RAG design, and model tuning.

Qualifications

• 2+ years of hands-on Data Science and NLP experience.
• Proficient in Python, LangChain, LLM orchestration, and API integration.
• Experience with vector databases and retrieval-augmented architectures.
• Knowledge of model evaluation, embeddings, and RAG.
• Familiar with cloud platforms and observability tooling.
• Experience deploying AI pipelines and tooling in production.
• Strong collaboration with product and engineering teams.
• Understanding of governance and reproducibility in AI systems.
• Ability to design scalable AI workflows and agent-based automation.

Responsibilities

• Build, evaluate, and optimize LLMs, knowledge-grounded models, and agentic pipelines.
• Develop multi-agent systems, tool-based agents, retrieval-augmented agents, and workflow automations.
• Implement LangChain, LangGraph, LLM flows or equivalent frameworks for orchestration.
• Fine-tune open-source LLMs (Llama, Mistral, Gemma) for domain-specific tasks.
• Design and deploy end-to-end AI pipelines from ingestion to inference & monitoring.
• Integrate LLM-based systems with external APIs, SaaS tools, and enterprise systems.
• Build reusable modules, prompt libraries, agent frameworks, and evaluation suites.
• Work closely with MLOps teams for optimization, caching, latency reduction, and cost control.
• Perform advanced prompt engineering, RAG tuning, embeddings design, and model evaluation.
• Design experiments, analyze model performance, and implement continuous improvement cycles.
• Develop structured datasets for LLM training, synthetic data generation, and data quality validation.
• Partner with architects to design scalable AI platform architecture.
• Translate business requirements into technical designs and AI workflows.
• Document solutions, maintain repos, and follow reproducibility & governance.

Skills

Python

LangChain

LangGraph

OpenAI APIs

Anthropic APIs

Google APIs

Agentic AI frameworks

LLM tuning

RAG architectures

Embedding models

Observability tools

Cloud platforms (AWS/Azure/GCP)

API integration & microservices

Education

Bachelor's degree in Computer Science or related field

Tools

Pinecone

Weaviate

Milvus

Chroma

Docker

Kubernetes

Job description

Job Description

Giniminds partners with organizations to transform them into real-time enterprises.

We specialize in AI-driven modernization - spanning data protection, real-time analytics, streaming platforms, information security, B2B integration, and enterprise application integration. With a strong partner ecosystem and a data-driven strategy, we deliver agile, scalable, and cutting-edge solutions that drive meaningful business outcomes.

Job Title: LLM Data Scientist (2+ Years Experience)

Employment Type: Full-time

About the Role

We are looking for an experienced LLM Data Scientist who can design, develop, and optimize Agentic AI systems and enterprise-grade AI platforms. The ideal candidate has hands‑on experience with LangChain, LLM orchestration frameworks, vector databases, and AI agents that automate complex business workflows. You will work closely with product, engineering, and AIOps teams to build scalable, production‑ready AI capabilities.

Key Responsibilities

LLM & Agentic AI Development

• Build, evaluate, and optimize LLMs, knowledge-grounded models, and agentic pipelines.
• Develop multi-agent systems, tool‑based agents, retrieval‑augmented agents, and workflow automations.
• Implement LangChain, LangGraph, LLM flows, or equivalent frameworks for orchestration.
• Fine‑tune open‑source LLMs (Llama, Mistral, Gemma, etc.) for domain‑specific tasks.
• Design and deploy end‑to‑end AI pipelines - from ingestion to inference & monitoring.
• Integrate LLM‑based systems with external APIs, SaaS tools, and enterprise systems.
• Build reusable modules, prompt libraries, agent frameworks, and evaluation suites.
• Work closely with MLOps teams for optimization, caching, latency reduction, and cost control.

Data Science & Model Engineering

• Perform advanced prompt engineering, RAG tuning, embeddings design, and model evaluation.
• Design experiments, analyze model performance, and implement continuous improvement cycles.
• Develop structured datasets for LLM training, synthetic data generation, and data quality validation.

Collaboration & Architecture

• Partner with architects to design scalable AI platform architecture.
• Translate business requirements into technical designs and AI workflows.
• Document solutions, maintain repos, and follow best practices for reproducibility and governance.

Required Skills & Experience

• 2+ years hands‑on experience in Data Science and NLP,LLM
• Strong experience in Python, LangChain, LangGraph, OpenAI / Anthropic / Google APIs, and agentic AI frameworks.
• Experience with vector databases (Pinecone, Weaviate, Milvus, Chroma).
• Knowledge of RAG architectures, retrieval optimization, embedding models, and observability tools.
• Familiarity with LLM tuning (LoRA, QLoRA, SFT, RLHF).
• Experience deploying models on cloud platforms (AWS, Azure, GCP) or on‑prem GPU clusters.
• Understanding of API integration, scalable microservices, and asynchronous job systems.

Preferred / Good to Have

• Experience building enterprise AI platforms, AI copilots, or workflow automation systems.
• Hands‑on exposure to agent frameworks like CrewAI, AutoGen, Haystack Agents, or custom tool‑based agents.
• Familiarity with LLM evaluation frameworks, hallucination detection, guardrails, and safety tooling.
• Experience with Docker, Kubernetes, and end‑to‑end CI/CD.

Soft Skills

• Strong problem‑solving and system thinking
• Ability to work in a fast‑paced environment
• Product mindset with focus on reliability and scalability

Why Join Giniminds

• Work on cutting‑edge Agentic AI & LLM platform initiatives
• Opportunity to build foundational AI components used across the organization
• Culture of innovation, experimentation, and ownership

Education

• Bachelor's degree in Computer Science, or related field.