Credence is seeking a Senior AI Software Engineer to design, develop, and deploy advanced AI-driven solutions for federal clients, including generative AI, large language models, retrieval-augmented generation, and agentic AI systems. You will collaborate with cross-functional teams across data, cloud, and mission stakeholders to deliver secure, scalable, mission-focused AI capabilities. Responsibilities include leading AI solution delivery, owning end-to-end agentic AI lifecycles (model selection, tool calling, orchestration, deployment), applying strong software engineering practices, conducting code reviews, and leveraging AI-assisted development tools responsibly. You will work with data engineers, software engineers, data scientists, cloud engineers, and stakeholders to translate needs into operational AI solutions; design and automate deployment using Infrastructure as Code (IaC), CI/CD pipelines, containers, and cloud-native services; monitor post-deployment performance and apply best practices for reliability and scalability. Document thoroughly and mentor teammates; stay current on emerging AI trends while contributing to reusable standards and design reviews. Qualifications include 7+ years of hands-on software engineering with AI/ML in production, experience with generative AI, LLMs, tool calling, evaluation, and retrieval-augmented generation; familiarity with agentic AI frameworks such as Agent2Agent Protocol, Bedrock Agents, Mastra, CrewAI, Strands, AgentCore, LangChain, or LangGraph; strong knowledge of AI APIs and platforms (OpenAI, Anthropic, Gemini, Amazon

Credence is seeking a Senior AI Software Engineer to design, develop, and deploy advanced AI-driven solutions for federal clients, including generative AI, large language models, retrieval-augmented generation, and agentic AI systems. You will collaborate with cross-functional teams across data, cloud, and mission stakeholders to deliver secure, scalable, mission-focused AI capabilities. Responsibilities include leading AI solution delivery, owning end-to-end agentic AI lifecycles (model selection, tool calling, orchestration, deployment), applying strong software engineering practices, conducting code reviews, and leveraging AI-assisted development tools responsibly. You will work with data engineers, software engineers, data scientists, cloud engineers, and stakeholders to translate needs into operational AI solutions; design and automate deployment using Infrastructure as Code (IaC), CI/CD pipelines, containers, and cloud-native services; monitor post-deployment performance and apply best practices for reliability and scalability. Document thoroughly and mentor teammates; stay current on emerging AI trends while contributing to reusable standards and design reviews. Qualifications include 7+ years of hands-on software engineering with AI/ML in production, experience with generative AI, LLMs, tool calling, evaluation, and retrieval-augmented generation; familiarity with agentic AI frameworks such as Agent2Agent Protocol, Bedrock Agents, Mastra, CrewAI, Strands, AgentCore, LangChain, or LangGraph; strong knowledge of AI APIs and platforms (OpenAI, Anthropic, Gemini, Amazon