AI (Python) Developer (Hybrid)

Job Description: DXC Technology (NYSE: DXC) helps global companies run their mission-critical systems and operations while modernizing IT, optimizing data architectures, and ensuring security and scalability across public, private, and hybrid clouds. The world’s largest companies and public sector organizations trust DXC to deploy services across the Enterprise Technology Stack to drive new performance levels, competitiveness, and customer experience. Learn more about how we deliver excellence for our customers and colleagues at DXC.com. ​ Clearance: Must be a US Citizen with an active Secret Security Clearance Work Environment: Hybrid, on-site 2-3 days, Cristal City, Arlington, VA Responsibilities Design, develop, test, and maintain AI agents and generative AI applications using Python. Develop agent workflows that use large language models to interpret user requests, reason across multiple steps, select appropriate tools, retrieve information, and generate grounded responses. Design, test, and iteratively refine system prompts, task instructions, tool-use instructions, few-shot examples, response formats, and other prompt-engineering components. Apply prompt-engineering techniques to improve response accuracy, consistency, grounding, tool selection, adherence to business rules, and overall user experience. Develop agent orchestration logic including state management, context management, tool selection, multi-step execution, retries, exception handling, and recovery. Develop Python application components using boto3, botocore, and other appropriate SDKs and libraries to interact with AI, data, storage, security, and supporting cloud services. Integrate agents with approved tools, APIs, Model Context Protocol (MCP) services, databases, knowledge sources, and enterprise applications. Work with AI Integration Engineers to define tool requirements, expected inputs and outputs, validation rules, and integration behaviors needed by AI agents. Build and optimize retrieval-augmented generation (RAG) capabilities including query formulation, retrieval logic, context assembly, grounding, semantic search, and use of retrieved information within agent workflows. Develop prompt and context strategies for working with structured and unstructured enterprise information while minimizing irrelevant or unsupported model responses. Implement structured outputs, schema validation, response validation, guardrails, error handling, and other controls required for reliable enterprise AI behavior. Develop reusable Python libraries, utilities, agent components, prompts, and development patterns that can be used across multiple AI use cases. Create automated unit, integration, regression, and AI evaluation tests covering agent workflows, prompts, tool selection, model responses, retrieval quality, and application behavior. Develop and maintain evaluation methods for response quality, factual grounding, hallucination, tool-use accuracy, retrieval effectiveness, latency, consistency, and regression. Analyze model and agent behavior using logs, prompts, responses, tool calls, retrieved context, and downstream results to identify and correct performance or reliability issues. Compare and evaluate models, prompting approaches, retrieval strategies, and agent designs based on accuracy, reliability, performance, maintainability, security, and suitability for the use case. Collaborate with functional experts and Product Owners to translate business problems into clearly defined AI use cases, expected behaviors, acceptance criteria, and measurable outcomes. Support demonstrations, user testing, defect resolution, production validation, monitoring, and continuous improvement of deployed AI capabilities. Maintain source code, prompts, technical designs, configuration, evaluation criteria, support documentation, and other AI development artifacts. Participate in code reviews, architecture discussions, backlog refinement, demonstrations, testing, release readiness, and other Agile/SAFe delivery activities. Other duties as assigned. Requirements Must possess an active Secret security clearance Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Information Systems, Engineering, or a related field; equivalent relevant experience may be considered. 3+ years of hands-on software development experience, including strong experience developing production-quality applications and services using Python. Strong Python development skills including object-oriented development, modules/packages, dependency management, exception handling, logging, testing, debugging, and API development. Hands-on experience developing AI agents, agentic workflows, LLM-based applications, or comparable generative AI capabilities. Strong hands-on prompt engineering experience, including development and refinement of system prompts, task instructions, few-shot examples, structured outputs, grounding strategies, tool-use instructions, and context-management approaches. Experience developing applications that interact with large language models through APIs or SDKs. Experience developing agent workflows that use tools, APIs, or MCP-based services, including tool selection, structured inputs and outputs, error handling, and integration of tool results into agent behavior. Hands-on experience using boto3 and botocore to develop applications that interact with cloud services and APIs. Experience with retrieval-augmented generation (RAG), semantic search, embeddings, vector search, or other knowledge-grounded AI techniques. Experience developing REST APIs, consuming APIs, working with JSON, and integrating Python applications with external services. Experience developing automated tests or evaluation methods for AI applications, including assessment of response quality, grounding, tool use, or regression behavior. Experience with Git/source control, cod