AI Platform Engineer

Job Title - Senior AI & Platforms Engineer

Role Overview

We are seeking a Senior Engineer to build and scale our next-generation AI platforms.

Key Responsibilities

• AI & Agentic Engineering: Design and implement autonomous multi-agent systems and cognitive architectures using cutting-edge agentic frameworks.
• Backend Architecture: Build high-performance, asynchronous Python microservices and robust REST/gRPC APIs.
• AIOps & CI/CD: Establish end-to-end MLOps/AIOps pipelines, automating the testing, deployment, and monitoring of AI models and data products.
• Data Infrastructure: Architect scalable data pipelines and query patterns across data platforms such as Snowflake/Databricks/Lakehouse.

Required Qualifications

• Python Expertise: good knowledge of advanced Python (Asyncio, FastAPI, Pytest) applied to distributed microservices.
• Agentic Frameworks: Hands-on experience developing with frameworks like LangGraph, CrewAI, AutoGen, or Semantic Kernel.
• Data Ecosystem: Deep technical proficiency with Snowflake, Databricks (Unity Catalog, Delta Lake), or Lakehouse architectures.
• DevOps & AIops: Proven track record building CI/CD pipelines (GitHub Actions, GitLab CI) and monitoring infrastructure (Prometheus, Grafana, MLflow).

Contract Position

Implementing Partner – HCL tech

Contract Position
Location – New York, NY
Duration: 6-9 months (possible extensions)

Job Summary: 

Senior AI & Platforms Engineer

Role Overview

We are seeking a Senior Engineer to build and scale our next-generation AI platforms.

Key Responsibilities

• AI & Agentic Engineering: Design and implement autonomous multi-agent systems and cognitive architectures using cutting-edge agentic frameworks.
• Backend Architecture: Build high-performance, asynchronous Python microservices and robust REST/gRPC APIs.
• AIOps & CI/CD: Establish end-to-end MLOps/AIOps pipelines, automating the testing, deployment, and monitoring of AI models and data products.
• Data Infrastructure: Architect scalable data pipelines and query patterns across data platforms such as Snowflake/Databricks/Lakehouse.

Required Qualifications

• Python Expertise: good knowledge of advanced Python (Asyncio, FastAPI, Pytest) applied to distributed microservices.
• Agentic Frameworks: Hands-on experience developing with frameworks like LangGraph, CrewAI, AutoGen, or Semantic Kernel.
• Data Ecosystem: Deep technical proficiency with Snowflake, Databricks (Unity Catalog, Delta Lake), or Lakehouse architectures.
• DevOps & AIops: Proven track record building CI/CD pipelines (GitHub Actions, GitLab CI) and monitoring infrastructure (Prometheus, Grafana, MLflow).