Senior Backend Python Jobs in Washington (NOW HIRING)

Job Summary:
Booz Allen Hamilton is seeking a Senior Backend Infrastructure & Agentic AI Platforms Software Development Engineer to build the next generation of agentic AI systems. The role involves owning the backend infrastructure and ensuring production reliability while working closely with a lean team to support clients in advancing AI-enabled systems within an R&D environment.
Responsibilities:
• Support backend infrastructure, agentic AI and protocol infrastructure, observability and production quality, and engineering excellence
• Own the end-to-end backend infrastructure on Microsoft Azure such as Azure Functions, Azure API Management, Azure Container Apps, and Azure OpenAI Service
• Own the data layer such as storage, retrieval pipelines, vector databases, and document indexing that power GRACE's internal knowledge search
• Own authentication and identity integration, including ARPA-H Entra ID and application-level access control, implement and maintain infrastructure as code for all environments, and no manual snowflakes
• Own CI/CD pipelines, deployment automation, and release processes including canary and gradual rollouts, own monitoring, alerting, logging, distributed tracing, SLOs, and incident response runbooks, and manage secrets, API keys, and credential rotation across all integrations with external providers
• Own cost and token economics across all LLM providers and track spend, analyze budgets, build guardrails, and optimize for cost-per-query without sacrificing quality
• Own the backend implementation of MCP, including MCP server hosting, tool registration, versioning, and lifecycle management on Azure and implement and evolve A2A communication patterns, enabling GRACE agents to interoperate with each other and with external agent systems
• Design and maintain LLM orchestration, routing, and multi-model switching infrastructure across OpenAI GPT, Anthropic Claude, and Google Gemini families and build and operate RAG pipelines, including document ingestion, chunking, embedding, and semantic search
• Implement robust fallback, retry, circuit-breaker, and graceful degradation patterns for all AI service dependencies and own tool-calling infrastructure, including registration, execution, error handling, and observability for all GRACE tools
• Build and maintain end-to-end observability for agentic workflows, including latency, throughput, error rates, token usage, and LLM quality metrics and implement LLM evaluation pipelines including safety checks, regression monitoring, and grounding assessment
• Define and enforce system-level SLOs for availability, response time, and tool call reliability and own alerting and on-call runbooks
• Establish and improve coding standards, design review processes, and testing practices and ensure strong privacy, security, and compliance in all systems, integrations, and data handling
• Communicate technical decisions clearly, in writing and in conversation, to both engineers and non-engineers
• Work backward from the user and understand the problem being solved before proposing a solution
Qualifications:
Required:
• 7+ years of experience with software engineering, including building and operating production systems
• Experience in high-velocity environments where you owned and shipped complex products end-to-end
• Experience with at least 2 backend languages, including Python
• Experience being on-call, debugging incidents, and writing the postmortem
• Experience with Microsoft Azure, including Azure Functions, API Management, Container Apps, and Azure OpenAI Service
• Experience with containerization, CI/CD, and infrastructure as code
• Knowledge of authentication and identity systems, such as OAuth2, OIDC, or Azure Entra ID
• Knowledge of modern backend frameworks and async patterns, distributed systems, APIs, data pipelines, and software design patterns
• Ability to own production systems
• Bachelor's degree in Computer Science or Software Engineering
Preferred:
• Experience building and operating MCP servers in production, including tool registration, versioning, and hosting on Azure Functions or equivalent serverless infrastructure
• Experience implementing A2A communication patterns and multi-agent orchestration frameworks
• Experience building on top of LLMs in production, including tool-calling, RAG, multi-step reasoning, multi-model routing, and context window management
• Experience in token economics, including cost-per-query, context budgets, and prompt efficiency as first-class engineering concerns
• Experience managing multi-provider LLM integrations including rate limits, fallback routing, and API versioning
• Experience in security-conscious engineering in regulated or government environments, including tracking record in startup or early-stage environments, including 0-to-1 product building
• Experience in big tech building customer-facing platforms or developer infrastructure at scale
• Knowledge of vector databases, embedding pipelines, and semantic search infrastructure
• Ability to be comfortable with ambiguity and a high sense of urgency, be a self-starter, operate within a fast-paced environment, multi-task, and handle multiple priorities
• Possession of excellent oral and written communication skills
Company:
Booz Allen Hamilton is a consulting firm that specializes in analytics, technology, and engineering. Founded in 1914, the company is headquartered in Mclean, USA, with a team of 10001+ employees. The company is currently Late Stage.