What are the responsibilities and job description for the Full Stack Java Technical Specialist - React.js position at HCLTech?
Durham, North Carolina
Job Summary
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.
Key Responsibilities
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
Skill Requirements
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)
Maximum Salary (US): 189000
Minimum Salary (US): 95000
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Job Summary
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.
Key Responsibilities
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
Skill Requirements
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)
Maximum Salary (US): 189000
Minimum Salary (US): 95000
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Benefits:
Health Insurance, Vacation & Paid Time Off, 401K PlanSalary : $189,000