AI / MLOps Architect

Siri InfoSolutions Inc; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Siri InfoSolutions Inc. seeks an experienced AI / MLOps Architect to design and deploy scalable AI/ML systems remotely. You will lead agent-based AI workflows, ML pipelines, and orchestration logic, collaborating with data scientists, ML engineers, DevOps, and software teams.

You will architect for AI/ML, LLM-based pipelines, vector memory, and RAG architectures, while driving technical strategy, tooling, and infrastructure decisions in a remote, global team.

Qualifications

• Proven experience architecting AI/ML systems and agent-based AI workflows.
• Hands-on experience with AI/ML pipelines, deployment, testing and validation.
• Strong knowledge of NLP, RAG, and vector databases.
• Experience with cloud ML platforms (GCP Vertex AI) and Kubeflow.
• Collaborative in Agile teams across data science, DevOps and software engineering.
• Retail domain experience is a plus.

Responsibilities

• Meet with IT and Business teams to understand requirements.
• Architect AI/ML systems and agent-based AI workflows.
• Lead design and development of AI/ML, MLOps, and agentic AI solutions.
• Develop and optimize ML models, pipelines, and orchestration.
• Deploy models, LLM pipelines, and vector memory systems.
• Collaborate with data scientists, ML engineers, DevOps and software engineers.
• Drive technical strategy and infrastructure decisions.
• Communicate status to management and meet objectives.
• Identify process improvements and cross-team coordination.

Skills

Python

Java

Agentic AI

LangChain

TensorFlow

PyTorch

AutoML

NLP

GCP Vertex AI

Kubeflow

RAG

Vector memory

GPU programming

TensorRT

GitHub

Agile

Tools

Gemini Tools

Custom MCP tools

DB2

Oracle

BigQuery

Bigdata

Cassandra

PostgreSQL

Job description

Role AI / MLOps Architect

Location Remote

Fulltime

Job Description

Must Have Technical/Functional Skills

• Programming Languages: Python, Java
• Agentic AI: Google ADK, A2A, LangChain/Lang Graph, Crew AI, Semantic Kernel/Autogen and Open AI Agentic SDK
• Tool Integration: Gemini Tools, Custom MCP tools
• Machine Learning Frameworks: Experience with TensorFlow, PyTorch and AutoML.
• Generative AI: Hands-on experience with generative AI models, RAG (Retrieval-Augmented Generation) architecture, and Natural Language Processing (NLP).
• Cloud Platforms: Google Cloud Platform (GCP), Vertex AI and Kubeflow
• Data Engineering: Proficiency in data pre-processing and feature engineering.
• Version Control: Experience with GitHub for version control.
• Data Science Practices: Skills in building models, testing/validation, and deployment.
• Databases: DB2, Oracle, BigQuery, Bigdata, Cassandra, PostGRES
• Collaboration: Experience working in an Agile framework.
• RAG Architecture: Experience with data ingestion, data retrieval, and data generation using optimal methods such as hybrid search.
• Good to Have: Knowledge in GPU programming, GPU profiling, GPU optimizations & TensorRT

Functional Skills -

• Experience working with customers in Retail Domain
• Knowledge in Retail Pricing functionalities is a plus

Roles & Responsibilities

• Meet with IT and Business teams to understand the requirements and opportunities
• Architect systems for AI/ML, agent-based AI workflows.
• Lead the design and development of AI/ML, ML Ops & Agentic AI solutions
• Develop and optimize ML models, pipelines, and orchestration logic
• Deploy AI/ML Models, LLM-based pipelines, agent orchestration, and vector-based memory systems
• Work closely with data scientists, ML engineers, DevOps, and software engineers to ensure seamless integration and deployment of solutions
• Drive technical strategy, tooling, and infrastructure decisions.
• Provides management with timely communication on status & utilizes appropriate tools and/or develops custom solutions as required to meet objectives.
• Identifies areas for process improvement.
• Maintains appropriate communication within the team and across various teams (i.e., internal and external).