Experience: 4.00 years

Salary: Confidential (based on experience)

Expected Notice Period: 15 Days

Shift: (GMT 05:30) Asia/Kolkata (IST)

Opportunity Type: Office ()

Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: BLU)

(*Note: This is a requirement for one of Uplers' client - BLU)

What do you need for this opportunity?

Must have skills required

Agentic Workflows, AI, LangChain, Docker, Python, Langraph, Vector DB, Document AI

BLU is Looking for:

AI Engineer

Location: Bangalore | Key Focus: Applied AI / LLM Engineering | Experience: 4–6 years

ABOUT Us

We are an intelligent layer global trade runs on.

A unified intelligent platform — the world’s first of its kind — We embed directly into exporter and importer workflows, eliminating the fragmented systems and document-heavy processes that have made trade complex, slow, and expensive. Empowering businesses to focus entirely on growth, while we handle the rest.

Our mission: make global trade as seamless as doing business locally.

THE OPPORTUNITY

We live across India’s key export hubs — and aggressively scaling into recent markets. This role sits at the centre of that ambition.

You will work directly with the founding team to design, build, deploy, and own the AI systems that power our platform.

The problems are concrete: extracting reliable data from messy, scanned trade documents, automating trade compliance checks that teams still run by hand, and running models inside regulated financial institutions, where data cannot leave their infrastructure.

What You’ll Do

- Design, build, and ship end-to-end LLM-powered features — RAG, agentic workflows, tool calling, and multi-step AI pipelines — using LangChain and LangGraph.

- Build and maintain production-grade AI services and APIs in Python and FastAPI.

- Design and optimize retrieval systems — document ingestion and chunking, embeddings, vector databases, hybrid search,



and reranking — that hold up at production scale.

- Work across commercial LLM APIs (OpenAI, Anthropic, Gemini) and open-source models (such as Llama, Qwen, and Mistral), selecting the right model for each task based on accuracy, latency, cost, and data-privacy needs.

- Fine-tune open-source LLMs and embedding models on domain data — from dataset preparation and training to evaluation against baselines.

- Deploy and serve models on GPU infrastructure — containerized with Docker, orchestrated on Kubernetes, and served through vLLM or equivalent — optimizing for throughput, latency, and cost.

- Establish evaluation and monitoring for AI features: define quality metrics, build evaluation sets, diagnose failure modes, and drive continuous improvements in accuracy and reliability.

What We’re Looking For

- Bachelor’s degree in Computer Science, Engineering, or a related quantitative discipline.

- years of experience building AI/ML systems, with at least 2 years building and shipping LLM-powered applications in production.

- Strong proficiency in Python, with hands-on experience building and containerizing production APIs using FastAPI and Docker.

- Demonstrated production experience with LangChain and LangGraph, RAG, agentic workflows, and tool calling.

- Hands-on experience with vector databases (such as pgvector, Qdrant, etc.) and production retrieval pipelines.

- Practical experience with open-source LLMs alongside commercial APIs, including fine-tuning with LoRA, QLoRA, or PEFT using PyTorch and Hugging Face Transformers.





- Experience serving LLMs on GPU machines with vLLM, TGI, or equivalent, including quantization, on Kubernetes and at least one major cloud platform (AWS, Azure, or GCP).

- Experience with MLOps/LLMOps practices — experiment tracking and model versioning (such as MLflow or Weights &
- Biases), CI/CD for models and prompts, and safe rollout and rollback of model updates.

- Experience with document AI — OCR, layout parsing, or data extraction from scanned documents.

- Experience with evaluation and observability tooling for production AI systems (such as LangSmith, Langfuse, or RAGAS).

- Clear communicator who works autonomously in a rapid-paced startup and can separate substance from hype.

Skills Required

Python

- FastAPI

- Docker

- LangChain / LangGraph

- RAG

- Vector Databases

- Agentic Workflows &
- Tool Calling

- LLM APIs (OpenAI, Anthropic, Gemini)

- Open-Source LLMs

- Fine-Tuning (LoRA / QLoRA)

- PyTorch

- Model Serving (vLLM)

- MLOps / LLMOps

- Kubernetes

- Document AI / OCR

- AI Evaluation &

- Observability

How to apply for this opportunity?

- Step 1: Click On Apply! And Register or Login on our portal.

- Step 2: Complete the Screening Form &
- Upload updated Resume

- Step 3: Increase your chances to get shortlisted & meet the client for the Interview!

About Uplers

Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.

(Note: There are many more opportunities apart from this on the portal. Depending on the assessments you explicit, you can apply for them as well).

So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

📌 AI Engineer (Bengaluru)
🏢 Uplers
📍 Bengaluru