BDB.AI · CAREERS

AI Engineer

LOCATION: Bengaluru, India

EXPERIENCE :3–5 years

OPENINGS : 2

EMPLOYMENT TYPE : Full-time

About BDB

BDB (Big Data BizViz) is a unified, low-code data, analytics, and decision-intelligence platform. The BDB Platform brings data pipelines, a medallion lakehouse, a governed semantic layer, data products, and agentic AI analytics together in a single product used by enterprise and government customers across telecom, BFSI, manufacturing, and the public sector. Our global R&D; hub is in Bengaluru, and the platform is engineered to run mission-critical, high-volume workloads under an ISO 27001:2022-certified operating model.

Role Overview

As an AI Engineer, you will build and operationalise the machine-learning and generative-AI backbone of the BDB Platform — from training, deployment, and monitoring pipelines to the agentic, semantic-layer-grounded AI (BDB Data Agents) that powers conversational analytics with grounded, zero-hallucination answers. You will work closely with data scientists (BDB DS Lab), platform, and product teams to take models and AI features from notebook to reliable, scalable production.

Key Responsibilities

- Build and maintain end-to-end AIOps pipelines — training, validation, deployment, monitoring, and automated retraining — with reproducibility and versioning across data, code, and models.
- Deploy and serve ML models at scale (batch and real-time), containerised and orchestrated on Kubernetes.
- Engineer GenAI / LLM capabilities — RAG pipelines, embeddings, vector search, and prompt / agent orchestration — grounded in BDB’s Kinetic Semantic Layer for accurate, governed answers.
- Contribute to BDB Data Agents: agentic,



conversational analytics grounded in the semantic layer and business ontology.
- Build feature-engineering and feature-store workflows, integrated with the platform’s data pipelines and lakehouse.
- Implement model and LLM monitoring — drift, performance, data quality, cost, and guardrails / evaluation.
- Optimise inference for cost and latency (GPU / CPU sizing, quantisation, caching, batching).
- Collaborate with data scientists, data engineers, and product to productionise models and AI features securely and reliably.

Must-Have Skills & Experience

- 3–5 years in MLOps / ML Engineering / AI Engineering.
- Python & engineering — strong Python with solid software-engineering fundamentals.
- ML frameworks — scikit-learn and PyTorch or TensorFlow.
- MLOps tooling — MLflow, Kubeflow, DVC, or equivalent.
- Model serving — FastAPI, BentoML, KServe, or Triton.
- Containers — Docker, with working knowledge of Kubernetes.
- GenAI / LLM — hands-on RAG, embeddings, vector databases (pgvector, Milvus, FAISS, or similar), and LLM / agent frameworks (LangChain, LlamaIndex, or equivalent).
- Cloud ML — Azure ML preferred.
- Data — comfortable with SQL; Spark / PySpark a plus.

Preferred/ Nice to have

- Agentic AI / multi-agent orchestration and tool-use.
- Grounding LLMs to structured data / semantic layers (text-to-SQL, semantic retrieval).
- Fine-tuning, prompt optimisation, and LLM evaluation frameworks.
- Real-time / streaming ML and online inference.
- Experience deploying AI for enterprise or regulated customers.

Pay: ₹900,000.00 - ₹1,800,000.00 per year

Benefits

- Versatile schedule
- Paid time off
- Provident Fund

Work Location: In person

📌 AI Engineer (Bengaluru)
🏢 BizViz Technologies
📍 Bengaluru