Full Stack Java Technical Specialist - React.js

HCL America Inc.

Durham, NC, United States

about 2 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Compensation

$189,000.0

Working hours

Regular working hours

Job source

indeed.com

Tech stack

Java (Programming Language) JavaScript (Programming Language) .NET Framework Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Software Applications Application Performance Management Microsoft Azure COBOL (Programming Language) Data Integration Extract Transform Load (ETL)

+34 more

DevOps Distributed Systems Graph Database Python (Programming Language) Neo4j Node.Js NoSQL Rapid Prototyping Process Cloud Services Software Engineering SQL Databases TypeScript Management of Software Versions Web Application Frameworks Data Logging Cloud Platform System GitHub Copilot ReactJS Large Language Models Grafana Prompt Engineering Apache Spark Generative AI Backend AngularJS Kubernetes Machine Learning Operations Front End Software Development Restful APIs Terraform Splunk Data Pipelines Serverless Computing Docker

Job description

We are seeking a Forward Deployment AI Engineer to join our innovation team focused on leveraging modern technologies, including Generative AI, to accelerate software development and deliver impactful solutions. In this role, you will work across the full stack, build prototypes and production-ready applications, and contribute to the design and implementation of AI-driven capabilities, including LLM-based solutions. You will collaborate with cross-functional teams to evaluate emerging technologies and translate ideas into scalable solutions that improve engineering productivity and business outcomes., Design, develop, and deploy end-to-end AI-powered applications across frontend, backend, and AI layers Build and integrate LLM-based solutions, including RAG pipelines and prompt engineering workflows Develop and consume REST APIs and implement seamless system integrations Build full-stack applications using modern frameworks (Python, Node.js, Angular/TypeScript) Design and manage data pipelines (ETL/ELT) and work with relational, NoSQL, and graph databases Deploy and manage applications in cloud environments (AWS/Azure/GCP) using core cloud services Ensure scalability, performance, and reliability of applications through effective system design Implement monitoring, logging, and evaluation mechanisms for AI and application performance Collaborate with business and technical stakeholders to translate requirements into technical solutions Contribute to rapid prototyping, innovation initiatives, and continuous improvement of engineering practices

Requirements

Do you have experience in TypeScript?, Programming & Software Engineering (Required)

Strong proficiency in Python (primary language) Experience in JavaScript / TypeScript Backend frameworks: Node.js / Angular Exposure to Java or .NET ecosystems Strong experience in SQL / NoSQL databases Experience with Graph Databases (Neo4j, Cypher)

Full-Stack & Integration API development and consumption (REST services) Frontend development (Angular / TypeScript) Data integration: APIs, workflows, and data orchestration Experience with data pipelines (ETL/ELT)

Cloud & DevOps (Hands-on Delivery Focus) Experience with at least one cloud: AWS / Azure / GCP Hands-on usage of core cloud services (compute, serverless, NoSQL, etc.)

AI / ML Specialization (Critical Requirement) Strong understanding of LLM fundamentals (transformers, prompting) Hands-on experience building RAG pipelines end-to-end

Other Requirements

Good to Have

Containers (Docker) and orchestration (Kubernetes) Infrastructure as Code (Terraform) Observability tools (Splunk, OpenTelemetry, tracing) Vector databases (Pinecone, Weaviate, PGVector) Frameworks: LangChain, LangGraph, LlamaIndex, CrewAI AI evaluation, guardrails, and observability MLOps fundamentals (deployment, monitoring, versioning) Responsible AI practices

Experience with Prompt Engineering Familiarity with AI coding assistants (GitHub Copilot, Codex) Exposure to mainframe / COBOL environments Participation in GenAI hackathons or rapid prototyping initiatives Understanding of basic distributed systems (Spark or equivalents)