Infrastructure Software Engineer Jobs in District of Columbia

Backend Infrastructure & Agentic AI Platforms Software Development Engineer, Senior

The Opportunity:

To achieve an organization’s mission, leaders need strong team members who can build the next generation of agentic AI to transform how clients accelerate research, makes decisions, and ships products at scale. That is why we need you, an experienced Software Development Engineer who can operate at a system-of-systems level to support clients in advancing AI-enabled systems within an R&D environment.

As part of our team, you'll serve as a Software Development Engineer to the Advanced Research Projects Agency for Health (ARPA-H). ARPA-H has a small team that is building the next generation of agentic AI to transform how the agency accelerates research, makes decisions, and ships products at scale. The team will evolve ARPA-H's production AI assistant into an ecosystem of autonomous, multi-agent systems.

You'll serve as a Software Development Engineer where you will own the backend infrastructure, while also being a first-principles builder of the agentic AI systems that run on top of it. On a lean team, infra and AI are not separate concerns. You will own both, and you will treat production reliability, token economics, security, and observability as non-negotiable from day one.

What You’ll Work On

• 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

Join us. The world can’t wait.

You Have:

• 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

Nice If You Have:

• 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

Compensation

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $86,800.00 to $198,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.

Identity Statement

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.

Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

• Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.

• Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.

• Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.