Cloud Developer with AI & Integrate large language models (LLMs)

Overview

On Site
Full Time

Skills

Java
Python
GCP
Amazon Web Services
Continuous Integration/Delivery
DEV OPS
Deployment
Machine Learning
C++
Data Management
Automated Testing
Provisioning
MCP
Networking
Workflow
Mentoring
Customer Engagement
Large-Scale
Structured Software
Serverless Architecture
Financial Services
B2B Software
Root Cause Analysis
Containerization
Distributed Systems
Logging

Job Details

Title: Cloud Developer with AI & Integrating large language models (LLMs)

Job Location:- Alpharetta, GA or Berkeley Heights, NJ (Day 1 Onsite, Candidate needs to come 5 days at the client Office)
Experience: 5+ years with 2-3 months in AI
No Of Opening: 3

Primary Responsibilities:

Leading the design, development, and implementation of an agentic customer engagement platform, leveraging the latest Generative AI capabilities

Collaborating with other development teams to integrate agents, tools, and cloud services, ensuring seamless functionality and efficient workflows

Monitoring, operating, and optimizing the solution for performance, customer satisfaction, and cost efficiency, ensuring high availability and responsiveness.

Develop and integrate autonomous, agents that can plan, execute, and monitor tasks across cloud platforms, including retrieval-augmented generation, tool use, and workflow automation

Participating in code reviews, technical discussions, and contributing to the overall architectural strategy of AI solutions

Integrate large language models (LLMs), vector search, and other ML capabilities to power conversational experiences and intelligent recommendations

Collaborate with software engineering and security teams to ensure new services and features are production-ready and meet reliability standards

Qualifications:

Familiarity with Agent Development Kit (ADK), Model Context Protocol (MCP) and strong skills in prompt engineering for optimizing Generative AI model outputs.

5+ years of experience in software development with proficiency in at least one programming language (e.g., Python, Go, Java, C++)

Experience administrating cloud platforms (AWS, Google Cloud Platform, Azure), including networking, security, containerization, storage, data management, and serverless technologies

Deep understanding of observability (monitoring, alerting, and logging) tools in cloud environments. Ability to set up and maintain monitoring dashboards, alerts, and logs

Familiarity with Continuous Integration/Continuous Deployment (CI/CD) tools for automated testing, deployments, provisioning, and observability

Ability to manage and respond to incidents, perform root cause analysis, and implement post-mortem reviews

Understanding and practical experience with MLOps principles for managing the machine learning lifecycle

Experience with data management and engineering principles in a cloud context

Additional Qualifications a Plus:

Experience working with enterprise-scale financial services or other regulated industries

5+ years of experience in SRE, DevOps, MLOps, infrastructure, or cloud engineering roles, preferably supporting large-scale, distributed systems.

Experience leading technical projects or mentoring junior engineers

Cloud Certifications: Certified Engineer, Developer, Architect, DevOps

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.