AI Engineer – Agentic Data Platform (Remote)

AI Engineer – Agentic Data Platform (Remote) Join to apply for the

AI Engineer – Agentic Data Platform (Remote)

role at

NXT LABS

Design and architect agentic AI pipelines and multi-agent systems for data ingestion, transformation, processing, and analytics.

Build and optimize

Lakehouse -based solutions on

Databricks , including ETL / ELT pipelines, Delta Lake storage, and ML model operationalization.

Implement and orchestrate AI Agents using tools such as

Google Vertex AI Agent Builder ,

Aera / AREA , or similar agentic platforms.

Integrate LLMs and foundation models into autonomous workflows for analytics and decisioning.

Develop, test, and deploy

RAG

pipelines and

LLMOps

workflows for domain-specific knowledge and reasoning tasks.

Implement best practices for prompt engineering, fine-tuning, responsible AI, and guardrails in production.

Collaborate with Data Engineering, MLOps, and Product teams to ensure scalability, performance, and security of the agentic platform.

Monitor performance and optimize deployed agents and AI workflows.

Key Responsibilities

Design and architect agentic AI pipelines and multi-agent systems for data ingestion, transformation, processing, and analytics.

Build and optimize

Lakehouse -based solutions on

Databricks , including ETL / ELT pipelines, Delta Lake storage, and ML model operationalization.

Implement and orchestrate AI Agents using tools such as

Google Vertex AI Agent Builder ,

Aera / AREA , or similar agentic platforms.

Integrate LLMs and foundation models into autonomous workflows for analytics and decisioning.

Develop, test, and deploy

RAG

pipelines and

LLMOps

workflows for domain-specific knowledge and reasoning tasks.

Implement best practices for prompt engineering, fine-tuning, responsible AI, and guardrails in production.

Collaborate with Data Engineering, MLOps, and Product teams to ensure scalability, performance, and security of the agentic platform.

Monitor performance and optimize deployed agents and AI workflows.

Required Skills & Qualifications

5–8 years of experience in

AI / ML Engineering, Data Engineering, or Applied AI

roles.

Strong expertise in

Databricks

(PySpark, Delta Lake, MLflow, Unity Catalog).

Hands-on experience with agentic frameworks and toolkits, such as :

Google Vertex AI Agent Builder

Aera / AREA Agentic Platform

OR open-source frameworks (LangChain, AutoGen, CrewAI, HuggingFace ecosystem)

Strong Python skills with experience developing scalable AI / ML applications.

Experience deploying LLMs,

RAG workflows , and working with vector databases (Pinecone, Weaviate, Chroma, BigQuery Vector Search).

Good understanding of

MLOps / LLMOps : CI / CD, model versioning, experiment tracking, model monitoring.

Familiarity with cloud environments (GCP preferred; AWS / Azure a plus).

Strong system design, problem-solving, and debugging abilities.

Nice-to-Have

Experience developing autonomous decisioning systems for manufacturing, supply chain, finance, or enterprise automation.

Exposure to streaming platforms such as

Kafka, Kinesis, Pub / Sub .

Knowledge of graph-based reasoning, enterprise knowledge models, or knowledge graphs.

Experience integrating with enterprise platforms such as

SAP, Salesforce, ServiceNow , etc.

Soft Skills

Excellent verbal and written communication.

Strong ownership mindset with the ability to work independently.

Ability to collaborate effectively with diverse technical and business teams.

Education

Bachelor’s or Master’s degree in

Computer Science, Software Engineering, Data Science, AI / ML , or other relevant fields (or equivalent experience).

Seniority level Mid-Senior level

Employment type Full-time

Job function Sales, General Business, and Education

Industries Wireless Services, Telecommunications, and Communications Equipment Manufacturing

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