Data Integration & LLM Engineer

About the Role

We are seeking a highly motivated

Software Engineer

with a strong foundation in

Java (Spring Boot) ,

data integration , and a growing expertise in

Large Language Models (LLMs) . This role is ideal for engineers who enjoy working at the intersection of

scalable data systems

and

AI-driven applications , building robust pipelines while also exploring cutting-edge generative AI solutions.

Key Responsibilities

Design and implement

data integrations

including APIs, SaaS connectors, and ETL / ELT pipelines to ensure reliable and scalable data flows.

Build and maintain backend services and applications using

Java (Spring Boot or equivalent frameworks) .

Develop

Python-based workflows

for AI / ML pipelines, experimentation, and automation scripting.

Integrate and experiment with

LLMs

(OpenAI, Anthropic, LLaMA, Mistral, etc.) for use cases such as retrieval-augmented generation (RAG), summarization, and intelligent data insights.

Implement

vector search solutions

using Pinecone, Weaviate, Milvus, or FAISS for LLM-backed applications.

Collaborate with product, data, and ML teams to design end-to-end solutions that combine

data engineering

with

AI capabilities .

Ensure systems meet high standards of

performance, scalability, security, and compliance .

Required Qualifications

Strong programming experience in

Java (Spring Boot or equivalent frameworks) .

Familiarity with

Python , particularly for

AI / ML workflows and scripting .

Proven experience with

data integrations : APIs, SaaS connectors, ETL / ELT pipelines.

Exposure to

LLMs

(OpenAI, Anthropic, LLaMA, Mistral, etc.) and associated frameworks (LangChain, LlamaIndex, Hugging Face Transformers).

Experience working with

databases (SQL / NoSQL)

and

vector search technologies

(Pinecone, Weaviate, Milvus, FAISS).

Preferred Skills

Knowledge of

cloud platforms

(AWS, GCP, or Azure) for deploying scalable systems and ML workloads.

Familiarity with

containerization and orchestration

(Docker, Kubernetes).

Understanding of

data governance, observability, and security best practices .

Interest in

generative AI advancements

and a passion for building practical applications on top of them.