Top Tech Jobs & Startup Jobs

Design, operate, and scale highly available Kubernetes platforms across cloud, on-premises, and edge environments. Manage networking, databases, storage, observability, security, infrastructure automation, and stateful workloads. Partner with engineering teams on platform standards, lead incident response and post-mortems, and address reliability and scalability risks. The role supports secure AI platform deployments for government customers and requires an active U.S. DoD Top Secret clearance.

Build proactive pipelines for technical and hard-to-fill roles across engineering, AI/ML, product, design, and DevOps. Partner with hiring managers on intake and sourcing strategy, use creative sourcing channels and AI tools, screen candidates, deliver market intelligence, track pipeline metrics, and improve recruiting processes while balancing quality, volume, and speed.

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 technical discovery and solution design for U.S. Government customers, translating AI capabilities into architectures, demos, and proofs-of-concept. Partner with Sales, Data Science, Engineering, and Product to produce decision-oriented artifacts, support proposals/RFPs, present to stakeholders, and manage concurrent engagements to drive mission adoption of Seekr's AI platform.

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.

Lead technical discovery and solution design for U.S. Government customers, translating AI capabilities into mission-aligned architectures, demos, and POCs. Partner with Sales, Data Science, Engineering, and Product to drive proposals, present to senior stakeholders, mentor junior staff, and deliver operationally viable, secure AI solutions.

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.