Senior Software Engineer
Title: Senior Software Engineer Location: San Francisco, CA; St. Louis, MO; New York, NY; Washington, DC
The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes:
- Create multi-layered guardrails around agents
- Optimize data retrieval for agents
- Orchestrate fleets of asynchronous agents
- Automatically alerts users to deviations in data
- Illustrating how an agent reached a decision
As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders.
You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers.
- Manage the full lifecycle of feature development from requirement definition to deployment on classified networks.
- Direct the orchestration of asynchronous agent fleets to meet mission requirements.
- Lead customer engagements to translate mission needs into technical requirements.
- Own the communication with stakeholders to ensure implementation meets defined acceptance criteria.
- Conduct technical reviews and identify risks within machine learning infrastructure and model serving.
- Drive the platform roadmap by providing technical specifications for Federal product offerings.
Ideally you will have:
- Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases
- Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
- Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
- AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial.
- Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
- Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment
- Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering