Jobs at Accrete AI

Build end-to-end frontend and backend features for an AI platform: design scalable APIs, integrate ML models, build user interfaces, improve reliability and performance, and own projects from concept through deployment.

As a Staff Engineer, you will design and build cloud-native systems using Python and microservices architecture, focusing on AI-native solutions and data pipelines while collaborating cross-functionally.

Develop AI-driven automation for government and national security workflows. Build and evaluate machine learning, LLM, NLP, data pipeline, and agentic systems; analyze complex datasets; create evaluation frameworks; and productionize reliable AI capabilities. Collaborate with engineers, mission specialists, and government users to translate ambiguous requirements into measurable solutions, demonstrate capabilities, gather feedback, and improve mission outcomes.

Develop rapid software prototypes combining frontend applications, data pipelines, APIs, AI/ML models, and automation workflows. Ingest, transform, and integrate structured and unstructured data using Python and SQL; experiment with LLMs, RAG, embeddings, and AI agents; and collaborate with engineers, data scientists, product teams, mission experts, and government customers. Translate ambiguous requirements into demonstrable solutions, evaluate technical approaches, document prototypes, support secure deployments, and identify candidates for productionization.

Develop knowledge management workflows and analytical visualizations, including dashboards, maps, reports, and charts, to support government mission users. Analyze structured and unstructured data, translate operational requirements into intuitive visual products, support user testing and training, and collaborate with engineers, data scientists, analysts, and customers to improve information access and decision-making.

Administer data management and analytics platforms, manage ingestion and data quality, analyze complex structured and unstructured datasets, and develop reports, dashboards, and analytical products. The role supports AI/ML workflows including NLP, semantic search, and information retrieval, while partnering with engineers and government customers. Responsibilities also include translating mission requirements into data solutions, troubleshooting systems, protecting classified data, and supporting demonstrations and deployments in customer environments.

Coordinates complex technology programs from planning through deployment, managing schedules, dependencies, risks, deliverables, technical teams, and government customer relationships. Translates customer and mission requirements into engineering plans, tracks contractual commitments, facilitates technical reviews and status meetings, and ensures compliance with security and operational requirements. Works across engineering, AI/ML, product, data, security, leadership, and government stakeholders to deliver projects successfully.

Build and troubleshoot data ingestion, transformation, ETL/ELT, and integration pipelines; administer data management platforms; implement data quality, governance, metadata, lineage, and lifecycle processes; automate workflows; support secure data systems; and work directly with government mission users to onboard datasets, resolve issues, and enable analytical and AI applications.

The role involves managing the entire recruitment lifecycle for technical and non-technical roles, building talent pipelines, analyzing recruitment metrics, and implementing employee engagement initiatives.

The Director of Business Development will drive go-to-market efforts, identify opportunities, manage outreach campaigns, support the sales team, and represent Accrete at industry events.

As an Applied Scientist, you'll develop advanced computer vision solutions using video data and Vision-Language Models, focusing on multimodal learning and real-world problem solving.

The Accountant I will manage daily accounting operations, support month-end closes, perform reconciliations, handle payroll entries, and ensure compliance with financial reporting standards.

The Senior DevOps Engineer leads cloud infrastructure and pipeline management, focusing on automation, CI/CD processes, system performance, and mentoring junior engineers.

General application to be considered for current and future roles across Accrete Government, spanning technical, operational, and business disciplines. Candidates should show ownership, strong communication, curiosity, and comfort in fast-paced environments. Some roles may require U.S. citizenship, security-clearance eligibility or an active TS/SCI clearance, and experience supporting federal customers.

Serve as the company's chief legal officer: lead corporate governance, negotiate and manage contracts, direct IP strategy and patent/trade secret protection, advise executives and the board, oversee M&A and licensing, manage outside counsel and legal budgets, ensure compliance with federal procurement, cybersecurity and data privacy regulations, and support crisis management and internal investigations.

Lead Forward Deployed Engineering to scale customer implementations of Accrete's AI platform from discovery to production. Build operating models, delivery standards, staffing plans, and playbooks; manage and mentor teams; partner with Product, Engineering, Research, and customers to ensure secure, reliable, and scalable deployments with measurable impact.

Lead end-to-end technical deployments with strategic customers: scope, design, build, integrate, and stabilize AI-powered full-stack systems. Work directly with customer teams to translate workflows into production-grade solutions, configure AI agents and retrieval pipelines, support rollout and monitoring, and provide product feedback to improve models and platform capabilities. Travel up to 50%.

Build and optimize scalable AI infrastructure and distributed systems for model training and inference. Integrate research into production, improve model efficiency, ensure reliability and security, collaborate with cross-functional teams, and maintain large-scale data pipelines.

Build end-to-end frontend and backend features for an AI platform: design UIs for model interaction, develop scalable APIs and services, integrate ML models, improve reliability and performance, and own projects from concept to deployment.

Develop a unified AI platform by designing and building scalable applications, improving platform performance, and collaborating with ML engineers.