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FDE with LLM

Dallas, TX, US • Posted 5 days ago • Updated 5 days ago

Contract W2

Contract Independent

12 Months

On-site

$70 - $80/hr

Fitment

Dice Job Match Score™

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Job Details

Skills

AI & Agentic
Java

Summary

FDE with LLM

Dallas, NJ, Charlotte Onsite

Key Responsibilities

Enterprise Integration & Architecture: Design, build, and maintain production-ready microservices using Java and Spring Boot, with high-performance event-driven pipelines powered by Apache Kafka.
Agentic AI & Knowledge Architecture: Build multi-agent workflows and complex orchestration pipelines using Lang Graph and Python. Model domain expertise using Knowledge Graphs to ground AI outputs in structured enterprise data.
ADLC Transformation: Champion and operationalize AI-Driven Software Development Life Cycle (ADLC) frameworks to accelerate engineering throughput, maintain high code quality, and automate automated testing/deployment loops.
Hands-on AI Tooling: Daily hands-on development leveraging AI coding agents and including in any one of the LLMs - Claude, Devin, and Antigravity CLI to automate complex code bases and workflow automation.
CoE Enablement & Standards: Establish best practices, architecture patterns, and governance frameworks for integrating GenAI and Agentic systems with existing core backend services across the organization.

Core Software Engineering (Must-Have)

Java & Spring Boot: Deep expertise in Java (12+ preferred), Spring Boot, Spring Cloud, RESTful APIs, and microservices design patterns.
Event-Driven Architecture: Strong hands-on experience with Apache Kafka (producers, consumers, stream processing, topic architecture, and fault tolerance).
Enterprise Delivery: Solid track record of deploying resilient, high-scale applications into production environments.

AI & Agentic Capabilities

Python Proficiency: Strong functional programming capability in Python for AI framework integration.
Agentic Frameworks: Hands-on experience building cognitive state machines or multi-agent systems using LangGraph (or similar orchestration frameworks like LangChain/AutoGPT).
Knowledge Graphs: Experience with graph databases (e.g., Neo4j, Amazon Neptune, NetworkX) or semantic tech (RDF, SPARQL, Cypher) to represent contextual enterprise knowledge.
Modern AI Engineering Tools: Deep hands-on experience using Claude (Claude 3.5 Sonnet / API workflows), Devin, or AntiGravity CLI for code generation, architectural refactoring, and automated development tasks.

Process & Frameworks

ADLC Exposure: Comprehensive understanding of AI-Driven Development Life Cycles moving beyond basic prompt engineering into automated task breakdown, AI-assisted code reviews, automated refactoring, and continuous integration.

Nice to Have

Experience with Vector Databases (Pinecone, Qdrant, Milvus) and hybrid search implementations (Graph + Vector / GraphRAG).
Exposure to cloud-native deployments (AWS, Azure, or Google Cloud Platform) using Kubernetes and Terraform.
Familiarity with evaluation frameworks for LLMs and agentic systems (e.g., Ragas, TruLens).

Thanks & Regards,

Pankaj Singh - Team Lead

Phone #

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.

Dice Id: RTX1c3114
Position Id: 9074650
Posted 5 days ago

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Pankaj Singh

Recruiter @ CA-One Tech Cloud Inc.

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