Jobs at Seekr Technologies

Leads strategic defense partnerships and aligns multiple mission-system programs into an enterprise portfolio strategy. Oversees AI capability insertion across ISR, C2, communications, and mission-integration programs from prototyping through testing and transition to programs of record. Manages executive relationships, capture activities, partner governance, demand generation, technical integration, risks, budgets, and cross-functional execution. Represents the company with defense integrators and government customers across classified programs and multiple agencies.

Build and operate scalable, secure, production-ready software for federal environments, including cloud, GovCloud, and air-gapped networks. Responsibilities include designing distributed systems, maintaining containers and CI/CD pipelines, debugging production issues, supporting accreditation, implementing observability and automated testing, collaborating with Product and AI engineers, and mentoring teammates. The role requires strong Python, database, API, Kubernetes, distributed systems, and security-focused engineering experience.

Lead technical discovery and solution design for U.S. Government customers adopting trusted AI platforms. Develop architectures, demonstrations, prototypes, and proof-of-concepts; translate mission needs into actionable implementation approaches; present to technical and executive stakeholders; collaborate with engineering, data science, and product teams; support sales, proposals, and capture efforts; and manage concurrent customer engagements.

Design, prototype, deploy, and integrate generative and predictive AI solutions for U.S. government customers. Develop agentic workflows, fine-tune LLMs, build customer-facing interfaces, research emerging AI capabilities, and translate technical concepts for customers and subject matter experts. Support pre-sales efforts and create both rapid proofs of concept and scalable long-term implementations.

Designs, prototypes, verifies, and fields ruggedized hardware platforms for AI/ML-driven ISR and C2 workloads. Responsibilities include FPGA, ASIC, GPU, and edge-compute development; hardware-software integration; firmware and edge MLOps; hardware testing and certification; technical documentation; and translating operational requirements into scalable, reusable defense solutions. The role collaborates across hardware, software, ML, systems architecture, and acquisition teams while meeting U.S. defense and cybersecurity standards.

Build and optimize scalable frontend applications for Seekr’s AI platform using React and Next.js. Collaborate with ML, backend, DevOps, QA, and Product Design teams to rapidly deliver performant web features. Contribute to technical direction, automated testing, API integration, deployments, and continuous improvement of frontend architecture and user experiences.

Leads and develops a software engineering team delivering scalable, secure, production-ready applications for federal environments. Owns technical direction, execution, architecture, deployment, accreditation, incident response, and engineering practices across cloud, restricted, and air-gapped networks. Partners with AI, product, program, security, and customer teams while hiring, coaching, and retaining engineers. Guides distributed systems, containerization, CI/CD, observability, automated testing, and AI-backed feature delivery.

Supports a C-suite executive by managing calendars, complex domestic and international travel, meetings, events, expenses, communications, visitors, and confidential records. Coordinates with senior executives, board members, government officials, military leaders, and external partners while handling shifting priorities and maintaining discretion. The role requires strong organizational, communication, judgment, and relationship-management skills, familiarity with government or military protocols, and hybrid on-site availability in Reston, Virginia.

Forward Deployed Engineers embed with client teams to operationalize AI prototypes into production systems. They design data pipelines and retrieval frameworks, fine-tune and deploy LLMs and agentic workflows, integrate AI agents across cloud and on-premises environments, and implement monitoring, guardrails, security, and performance optimization. The role also involves client collaboration, troubleshooting model behavior, and creating reusable deployment practices. Travel may range from 25% to 75%.

Build and operate secure, scalable software for federal environments, collaborating with AI engineers to productionize applications across cloud, GovCloud, and air-gapped networks. Responsibilities include architecture, containerization, CI/CD, accreditation, observability, production debugging, testing, technical standards, requirements decomposition, and mentoring. The role requires strong Python, distributed systems, database, API, Kubernetes, and security-control expertise, plus experience delivering AI-backed features.

Lead end-to-end commercial and technical engagements to translate enterprise business problems into production-grade, explainable AI solutions. Define requirements, scope deployments, partner with engineers and designers, quantify business impact and ROI, drive adoption and training, and act as trusted advisor during implementation and change management.

Lead product strategy and roadmap for AI Ready Data capabilities—data ingestion, transformation, enrichment, synthetic data, and tooling for retrieval, fine-tuning, evaluation, and agent workflows. Write product specs, partner with engineering, research, design, and GTM, translate experiments into scalable features, work with customers to surface requirements, and define success metrics to monitor adoption and performance.

Design, prototype, deploy, and support generative and predictive AI solutions for U.S. Government customers. Develop interfaces and applications, agentic workflows, and LLM fine-tuning capabilities; research emerging AI techniques; translate technical concepts for customers and subject matter experts; and support pre-sales activities. The role requires Python development, AI/ML modeling, RAG technologies, LLM frameworks, APIs, and government-sector experience.

Embed with client teams to productionize AI: design data pipelines and retrieval frameworks, fine-tune and deploy LLMs and agentic workflows, containerize and orchestrate across cloud and on-prem, optimize inference and monitoring, and codify deployment best practices to scale trustworthy, explainable AI solutions.

Lead and hands-on manage Seekr's AI infrastructure: design, build, and scale Kubernetes-based systems across cloud, on-prem, and edge; mentor engineers; automate operations; handle incidents and security; collaborate with software teams to ensure reliability, performance, and observability.

Design and build explainable and contestable AI capabilities for models and agents. Develop hallucination detection, continual-learning systems, and production AI features from research prototypes. Contribute across model development, inference, deployment, monitoring, evaluation, and performance optimization. Partner with product, design, and customer teams to deliver trustworthy AI workflows. The role requires strong Python and software engineering skills, modern AI systems experience, and the ability to bridge research and production engineering.

Design and productionize explainable and contestable AI capabilities for LLM, VLM, agent, and RAG systems. Develop hallucination mitigation, continual-learning, evaluation, inference, deployment, monitoring, and retrieval solutions. Translate research into production features, optimize model serving, and collaborate with product, design, and customer teams. The role requires strong Python and software engineering skills, research-to-engineering fluency, and experience evaluating complex AI tradeoffs.

Lead the reliability, stability, observability, and scalability of Seekr’s software platform. Design and implement systems, networks, and services that meet SLAs; develop monitoring, automation, and failure-detection solutions; conduct load testing; manage observability tools; troubleshoot production and deployment issues; and support incident response. Collaborate closely with software engineering teams across hybrid cloud and on-premises environments.

Build and scale applications and tools powering AI products, agents, and enterprise solutions. Responsibilities include shipping production-ready features, shaping scalable and reliable architecture, mentoring engineers, driving technical decisions and engineering best practices, collaborating with Product, QA, and business teams, and translating abstract ideas into actionable engineering work. The role requires expertise in Python, distributed systems, APIs, databases, containers, streaming technologies, testing, CI/CD, and AI-assisted development.

Build SeekrFlow Edge Builder, a platform for packaging, deploying, and operating trustworthy AI solutions across edge, cloud, on-premises, disconnected, and air-gapped environments. Responsibilities include developing orchestration, lifecycle management, model serving, optimization, security, observability, testing, APIs, diagnostics, and recovery capabilities. The role requires collaboration across AI, platform, infrastructure, security, product, and customer engineering teams, plus technical documentation and troubleshooting across complex deployment environments.