LLM/Prompt-Context Engineer Fullstack Python

Job Title: LLM/Prompt-Context Engineer Fullstack Python (AI Agents, LangGraph, Context Engineering)

Location 1st Atlanta, 2nd Dallas, 3rd Seattle (Onsite no remote)

Duration: Long term

Face to Face interview

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: Prompt & Context Engineering: Design, optimize, and evaluate prompts for LLMs to achieve precise, reliable, and contextually relevant outputs across a variety of use cases. Context Management: Architect and implement dynamic context management strategies, including session memory, retrieval-augmented generation, and user personalization, to enhance agent performance. LLM Integration: Integrate, fine-tune, and orchestrate LLMs within Python-based applications, leveraging APIs and custom pipelines for scalable deployment. LangGraph & Agent Flows: Build and manage complex conversational and agent workflows using the LangGraph framework to support multi-agent or multi-step solutions. Fullstack Development: Develop robust backend services, APIs, and (optionally) front-end interfaces to enable end-to-end AI-powered applications. Collaboration: Work closely with product, data science, and engineering teams to define requirements, run prompt experiments, and iterate quickly on solutions. Evaluation & Optimization: Implement testing, monitoring, and evaluation pipelines to continuously improve prompt effectiveness and context handling. Required Skills & Qualifications: Deep experience with fullstack Python development (FastAPI, Flask, Django; SQL/NoSQL databases). Demonstrated expertise in prompt engineering for LLMs (e.g., OpenAI, Anthropic, open-source LLMs). Strong understanding of context engineering, including session management, vector search, and knowledge retrieval strategies. Hands-on experience integrating AI agents and LLMs into production systems. Proficient with conversational flow frameworks such as LangGraph. Familiarity with cloud infrastructure, containerization (Docker), and CI/CD practices. Exceptional analytical, problem-solving, and communication skills. Preferred: Experience evaluating and fine-tuning LLMs or working with RAG architectures. Background in information retrieval, search, or knowledge management systems. Contributions to open-source LLM, agent, or prompt engineering projects. Thanks & Regards Tech Mahindra is an Equal Employment Opportunity employer. We promote and support a diverse workforce at all levels of the company. All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, age, national origin or disability. All applicants will be evaluated solely on the basis of their ability, competence, and performance of the essential functions of their positions with or without reasonable accommodations. Reasonable accommodations also are available in the hiring process for applicants with disabilities