Ai ML Engineer

Saguna Consulting Services

United States

Remote

USD 120,000 - 180,000

Full time

14 days+

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Job summary

Saguna Consulting Services is seeking an experienced AI Engineer to design, build, and deploy enterprise AI/ML and Generative AI solutions. The role requires taking AI from PoC to production, focusing on architecture, development, integration, deployment, scalability, monitoring and ongoing optimization.

You will work with models like GPT, Llama, Claude and Mistral, design scalable RAG pipelines and embeddings, and build AI Agents using LangChain, LangGraph, CrewAI or AutoGen.

Qualifications

5+ years in AI/ML Engineering or Generative AI.
Hands-on enterprise AI deployment experience.
Proficiency in Python.
Experience with LLMs / Generative AI.
Familiarity with RAG, embeddings, vector databases.
Experience with Docker / Kubernetes / CI/CD.
Cloud: AWS / Azure / GCP.
APIs, microservices and enterprise integration.

Responsibilities

Design, develop and deploy enterprise-grade AI/ML and Generative AI solutions.
Build and integrate LLM-based applications, AI Agents and RAG solutions into enterprise workflows.
Work with models such as GPT, Llama, Claude, Mistral or equivalent foundation models.
Design scalable RAG pipelines, embeddings and vector-search solutions.
Develop AI Agents using LangChain, LangGraph, CrewAI, AutoGen or similar frameworks.
Integrate AI capabilities with existing enterprise applications, APIs, databases and business systems.
Optimize AI applications for performance, scalability, reliability, latency and cost.
Implement model deployment, monitoring, evaluation and continuous improvement using MLOps practices.
Build production-ready APIs, microservices and cloud-based AI applications.
Work with cloud platforms such as AWS, Azure or GCP, along with Docker, Kubernetes and CI/CD.
Collaborate with architects, engineering teams, product/business stakeholders and clients to translate business requirements into AI solutions.

Skills

AI/ML Engineering

Generative AI

LLMs

RAG embeddings

MLOps

Cloud computing

APIs/microservices

Docker/Kubernetes

Tools

LangChain

LangGraph

CrewAI

AutoGen

Job description

Role Overview

We are looking for an experienced AI Engineer with strong enterprise-level AI implementation experience. The ideal candidate should have hands‑on experience designing, building, integrating, and deploying AI/ML and Generative AI solutions into real-world enterprise environments.

The candidate should be able to take AI solutions beyond PoC — from architecture and development through integration, deployment, scalability, monitoring, and production optimization.

Key Responsibilities

Design, develop and deploy enterprise-grade AI/ML and Generative AI solutions.
Build and integrate LLM-based applications, AI Agents and RAG solutions into enterprise workflows and applications.
Work with models such as GPT, Llama, Claude, Mistral or equivalent foundation models.
Design scalable RAG pipelines, embeddings and vector-search solutions.
Develop AI Agents using LangChain, LangGraph, CrewAI, AutoGen or similar frameworks.
Integrate AI capabilities with existing enterprise applications, APIs, databases and business systems.
Optimize AI applications for performance, scalability, reliability, latency and cost.
Implement model deployment, monitoring, evaluation and continuous improvement using MLOps practices.
Build production‑ready APIs, microservices and cloud‑based AI applications.
Work with cloud platforms such as AWS, Azure or GCP, along with Docker, Kubernetes and CI/CD.
Collaborate with architects, engineering teams, product/business stakeholders and clients to translate business requirements into AI solutions.