Prompt Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
September 16, 2025
πŸ•’ - Project duration
More than 6 months
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🏝️ - Location type
On-site
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Atlanta, GA
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🧠 - Skills detailed
#Python #FastAPI #Flask #NoSQL #Deployment #Databases #Cloud #Monitoring #Data Science #Scala #SQL (Structured Query Language) #Django #Docker #AI (Artificial Intelligence)
Role description
Hi , Integration Engineer / Backend/Agent Engineer /LLM/Prompt-Context Engineer Seattle, Dallas, Atlanta, (Onsite from Day 1) 12+ months contract Drive on Thursday 18-Sep-2025 Total 3 Positions looking with Python Full stack Developer (AI Agents, LangGraph, Context Engineering) Position Overview: We are looking for a highly skilled LLM/Prompt-Context Engineer with a strong fullstack Python background to design, develop, and integrate intelligent systems focused on large language models (LLMs), prompt engineering, and advanced context management. In this role, you will play a critical part in architecting context-rich AI solutions, crafting effective prompts, and ensuring seamless agent interactions using frameworks like LangGraph. Key Responsibilities: β€’ Prompt & Context Engineering: Design, optimize, and evaluate prompts for LLMs to achieve precise, reliable, and contextually relevant outputs across a variety of use cases. β€’ Context Management: Architect and implement dynamic context management strategies, including session memory, retrieval-augmented generation, and user personalization, to enhance agent performance. β€’ LLM Integration: Integrate, fine-tune, and orchestrate LLMs within Python-based applications, leveraging APIs and custom pipelines for scalable deployment. β€’ LangGraph & Agent Flows: Build and manage complex conversational and agent workflows using the LangGraph framework to support multi-agent or multi-step solutions. β€’ Fullstack Development: Develop robust backend services, APIs, and (optionally) front-end interfaces to enable end-to-end AI-powered applications. β€’ Collaboration: Work closely with product, data science, and engineering teams to define requirements, run prompt experiments, and iterate quickly on solutions. β€’ Evaluation & Optimization: Implement testing, monitoring, and evaluation pipelines to continuously improve prompt effectiveness and context handling. Required Skills & Qualifications: β€’ Deep experience with fullstack Python development (FastAPI, Flask, Django; SQL/NoSQL databases). β€’ Demonstrated expertise in prompt engineering for LLMs (e.g., OpenAI, Anthropic, open-source LLMs). β€’ Strong understanding of context engineering, including session management, vector search, and knowledge retrieval strategies. β€’ Hands-on experience integrating AI agents and LLMs into production systems. β€’ Proficient with conversational flow frameworks such as LangGraph. β€’ Familiarity with cloud infrastructure, containerization (Docker), and CI/CD practices. β€’ Exceptional analytical, problem-solving, and communication skills. Preferred: β€’ Experience evaluating and fine-tuning LLMs or working with RAG architectures. β€’ Background in information retrieval, search, or knowledge management systems. β€’ Contributions to open-source LLM, agent, or prompt engineering projects. Gaurav Mote | Tekgence Inc Direct: 469-575-8666, Ext- 145 β€’ gaurav.mote@tekgence.com 6655 Deseo Dr, Suite 104, Irving, TX , 75039 β€’ www.tekgence.com Tekgence is an equal opportunity employer. Applicants must be authorized to work in the U.S. U.S. citizens and Green Card holders are strongly encouraged to apply.