| Location | Jacksonville, FL |
| Job Type | Contractor |
| Salary | $60–$64 Per Hour |
JOB TITLE: Sr. Python Developer
JOB LOCATION: Jacksonville, FL Hybrid
WAGE RANGE*: 60- 64/ hour must be W2
JOB NUMBER: 21186
JOB DESCRIPTION
Role Overview are seeking an experienced Senior Generative AI / Platform Engineer to lead the architecture, development, and scaling of our next-generation AI orchestration platform.
In this role, you will bridge the gap between cutting-edge AI research and robust enterprise infrastructure.
You will be responsible for designing advanced Retrieval-Augmented Generation (RAG) pipelines, building resilient AI Agents, implementing cutting-edge interoperability protocols like MCP, and pioneering multi-agent (Agent-to-Agent) collaboration networks.
Core Responsibilities:
• Hybrid Cloud Infrastructure & Deployment: Architect, deploy, and scale GenAI services, vector databases, and model gateways across a hybrid environment utilizing on-premises Red Hat OpenShift and public cloud services in AWS (e.g., EKS, Bedrock, EC2).
• Advanced RAG & Retrieval Optimization: Design and optimize enterprise RAG pipelines.
• Implement advanced retrieval strategies, including hybrid search (vector + lexical) and high-precision reranking workflows (using cross-encoders) to minimize LLM context noise, optimize token usage, and eliminate hallucinations.
• Agentic Systems & Tool Orchestration: Build, deploy, and monitor production-grade AI Agents capable of autonomous planning, tool usage, complex multi-step reasoning, and self-correction.
• Context Integration & Interoperability: Architect scalable integrations between LLMs and enterprise data silos using the Model Context Protocol (MCP), establishing clean, standardized interfaces for tool servers and data sources.
• Multi-Agent Networks (A2A): Design and implement Agent-to-Agent (A2A) collaboration systems, enabling specialized, decoupled agents to communicate, delegate tasks, and negotiate state synchronously or asynchronously.
• Enterprise Integration & Backend Development: Build secure, high-throughput, and fault-tolerant microservices in Java/Spring Boot to serve GenAI features, manage data orchestration, and expose robust endpoints.
Equal opportunity employer as to all protected groups, including protected veterans and individuals with disabilities
* While an hourly range is posted for this position, an eventual hourly rate is determined by a comprehensive salary analysis which considers multiple factors including but not limited to: job-related knowledge, skills and qualifications, education and experience as compared to others in the organization doing substantially similar work, if applicable, and market and business considerations. Benefits offered include medical, dental and vision benefits; dependent care flexible spending account; 401(k) plan; voluntary life/short term disability/whole life/term life/accident and critical illness coverage; employee assistance program; sick leave in accordance with regulation. Benefits may be subject to generally applicable eligibility, waiting period, contribution, and other requirements and conditions. Benefits offered are in accordance with applicable federal, state, and local laws and subject to change at TCM's discretion.
REQUIRED EXPERIENCE:
Hybrid Cloud & Container Orchestration: Red Hat OpenShift: Deep hands-on experience deploying, managing, and troubleshooting containerized enterprise applications in an on-premises OpenShift environment (including managing security contexts, routes, and cluster resources).
• AWS Platform: Strong expertise with core AWS infrastructure and AI/ML services (e.g., IAM, VPC, Amazon Bedrock, EKS, RDS).Dual-Stack Mastery (Python & Java):Python: Expert-level proficiency for AI/ML tasks, asynchronous programming, and data engineering. Java: Deep experience building distributed microservices utilizing the Spring Boot ecosystem (Spring Web, Spring Security, Spring Data).
• Generative AI Frameworks: Practical experience with orchestrating frameworks such as LangChain, LlamaIndex, LangGraph, AutoGen, CrewAI, LangChain4j, or Spring AI.
• Advanced RAG Stack: Experience with vector databases (e.g., Pinecone, Qdrant, Milvus, pgvector) alongside dedicated reranking APIs (such as Cohere Rerank, BGE, or open-source cross-encoders).
• Protocols & Standards: Solid understanding of MCP (Model Context Protocol) or experience building universal API layer abstractions for LLM tool utilization. MLOps, DevSecOps & Observability: Familiarity with LLM evaluation frameworks, CI/CD pipelines targeting OpenShift/AWS, and enterprise observability tools (e.g., Prometheus, Grafana, OpenTelemetry, LangSmith).
Required Work Experience:
5+ years related work experience, Professional experience with technical design and coding in the IT industry
Required Education:
Related Bachelor's degree or additional, related work experience
Preferred Qualifications
• Experience configuring on-prem OpenShift clusters with GPU acceleration (NVIDIA GPU Operator) for local LLM or embedding model hosting.
• Relevant certifications such as Red Hat Certified Specialist in OpenShift or AWS Certified Solutions Architect / Machine Learning Specialty.
• Active contribution to open-source GenAI projects, MCP servers, or multi-agent ecosystem tools.
The ideal candidate possesses deep expertise in Python for AI/LLM orchestration, a strong backend foundation in Java (Spring Boot), and proven experience deploying and managing containerized workloads across a hybrid-cloud topology consisting of on-premises Red Hat OpenShift and Amazon Web Services (AWS).