Full Stack Engineer (AI)
BAMM MED STAFFING LLC
Hoboken, NJ, United States
10 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source
Tech stack
Clean Code Principles
Java (Programming Language)
Application Programming Interfaces (APIs)
Agile Methodology
Artificial Intelligence
Amazon Web Services
Application Integration Architecture
Software Applications
Automation of Tests
Cloud Computing
Cloud Engineering
Software Quality
+30 more
Code Review
Databases
Continuous Delivery
Continuous Integration
Software Design Patterns
Elasticsearch
Python (Programming Language)
Machine Learning
MongoDB
Oracle (Applications)
Scrum Methodology
Queueing Systems
Secure Coding
Software Engineering
SQL Databases
Strategies of Testing
Toolchain
Chatbots
ReactJS
Retrieval-Augmented Generation
AI Coding Agents
Backend
Agentic-AI
Event Driven Architecture
Non-relational Database
Graphql
Front End Software Development
Restful APIs
Code Restructuring
Automation Anywhere
Job description
- Lead the design, development, and delivery of full stack AI-enabled applications and Conversational AI.
- Provide technical leadership across frontend, backend, API, database, and AI integration workstreams.
- Architect scalable, maintainable, and secure solutions using React, Python, Java, REST APIs, GraphQL, and database technologies.
- Guide the implementation of AI agents, AI workflows, RAG and intelligent automation capabilities.
- Establish and promote engineering best practices, including clean code, reusable components, automated testing, CI/CD, and design patterns.
- Drive integration with relational and non-relational databases, including SQL, Oracle, ElasticSearch and MongoDB.
- Collaborate with Agile SCRUM teams through sprint planning, backlog refinement, daily standups, demos, and retrospectives.
- Stay current with emerging AI, GenAI, full stack, and cloud-native engineering trends, and assess practical adoption opportunities.
- Experience with message queues, streaming platforms, pub/sub models, or event-driven architectures.
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Requirements
- Minimum of 5+ years of full stack application development experience.
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in REACT and one or more programming language(s)
- Proficiency in automation and continuous delivery methods
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Practical cloud native experience ex. AWS
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
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