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It starts with you - a senior AI engineer focused on building production-grade agentic systems: autonomous agents, MCP tools, agentic workflows, and rigorous evaluation.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Design and build single- and multi-agent systems with planning, memory, and tool use.
Implement and operate MCP tools and servers with secure schemas and permissions.
Build agentic workflows using LangChain, LangGraph, or equivalent frameworks.
Integrate LLMs via SDKs; manage prompts, structured outputs, and tool calling.
Define and run LLM evals (quality, correctness, latency, cost, regressions).
Add observability and reliability (logging, tracing, retries, state management).
Optimize performance and cost; take systems to production.
Mentor engineers and establish agentic best practices.

It starts with you - ML Engineering Team Lead responsible for leading a team delivering end-to-end ML systems. This role combines people management with ownership of model training, evaluation, deployment, and ML platform standards
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Lead and mentor ML Engineers delivering production ML systems.
Own technical direction for model architectures, training pipelines, and evals.
Review designs and code; ensure scalability, reliability, and data quality.
Define standards for experimentation, reproducibility, and monitoring.
Partner with product and platform teams on roadmap and prioritization.
Balance hands-on technical contribution with people management.
Build a culture of measurement, rigor, and continuous improvement.

At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Responsibilities
Conduct hands-on research and development of cutting-edge models
Take research projects from ideation to deployment and production
Work closely with domain experts and the engineering department to improve and create new innovative solutions.
Help define the AI product roadmap.

It starts with you - an engineer driven to build modern, real-time data platforms that help teams move faster with trust. You care about great service, performance, and cost. Youll architect and ship a top-of-the-line open streaming data lake/lakehouse and data stack, turning massive threat signals into intuitive, self-serve data and fast retrieval for humans and AI agents - powering a unified foundation for AI-driven mission-critical workflows across cloud and on-prem.
If you want to make a meaningful impact, join our companys mission and build best-in-class data systems that move the world forward - this role is for you.
The Responsibilities
Build self-serve platform surfaces (APIs, specs, CLI/UI) for streaming and batch pipelines with correctness, safe replay/backfills, and CDC.
Run the open data lake/lakehouse across cloud and on-prem; enable schema evolution and time travel; tune partitioning and compaction to balance latency, freshness, and cost.
Provide serving and storage across real-time OLAP, OLTP, document engines, and vector databases.
Own the data layer for AI - trusted datasets for training and inference, feature and embedding storage, RAG-ready collections, and foundational building blocks that accelerate AI development across the organization.
Enable AI-native capabilities - support agentic pipelines, self-tuning processes, and secure sandboxing for model experimentation and deployment.
Make catalog, lineage, observability, and governance first-class - with clear ownership, freshness SLAs, and access controls.
Improve performance and cost by tuning runtimes and I/O, profiling bottlenecks, planning capacity, and keeping spend predictable.
Ship paved-road tooling - shared libraries, templates, CI/CD, IaC, and runbooks - while collaborating across AI, ML, Data Science, Engineering, Product, and DevOps. Own architecture, documentation, and operations end-to-end.

It starts with you - an engineer driven to operate database systems at the highest level of reliability and performance. You care about query latency, uptime, data durability, and getting paged as little as possible. Youll operate, tune, and scale the database engines that serve the platform - from PostgreSQL to Elasticsearch, Redis to vector databases, across cloud and on-prem environments.
If you want to run the databases that power mission-critical AI at national scale, join our companys mission - this role is for you.
The Responsibilities
Operate and maintain database systems - PostgreSQL, Elasticsearch, Redis, MongoDB, vector databases, and others across cloud and on-prem.
Own database reliability - high availability configurations, replication, failover automation, and SLA adherence.
Drive performance tuning - query optimization, index design, configuration tuning, and resource profiling to meet latency and throughput targets.
Execute operational procedures - backup/recovery, disaster recovery testing, upgrades, migrations, and capacity scaling.
Lead incident response for database issues - troubleshooting production problems, root cause analysis, and implementing preventive measures.
Build monitoring and alerting - dashboards, metrics collection, slow query analysis, and proactive capacity alerts.
Enable new capabilities - deploying and tuning vector databases for AI workloads, evaluating new database technologies.
Collaborate with Data Platform, Data Engineering, Engineering, and Security teams on database operations and best practices.
Uphold database SLAs that support retrieval paths, feature stores, and embedding durability; coordinate safe schema evolution, partitioning, and replay/backfill practices.
Expose catalog and lineage signals - ownership, change history, and impact analysis - to improve trust and safe consumption for downstream users.
Collaborate with Data Platform, Data Engineering, Engineering, Security, Product, AI/ML, Data Science, and Analytics to balance performance, durability, and evolution across workloads.

At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Responsibilities
Conduct hands-on research and development of state-of-the-art models, algorithms, and systems.
Lead research projects end-to-end from problem formulation, ideation, and experimental design to prototyping and transition into production.
Explore new methodologies and develop creative approaches to solve complex challenges.
Identify ambitious research directions and invent novel approaches to solve complex, high-impact problems.
Shape the research roadmap and influence long-term technical strategy across the organization.

It starts with you - a senior ML engineer responsible for building, training, evaluating, and operating machine learning systems in production. The role focuses on data pipelines, model training, experimentation, evaluation, and scalable deployment.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Design, train, and evaluate ML models for production use.
Build and maintain data pipelines for training, validation, and inference.
Own experimentation workflows: feature engineering, training runs, and comparison.
Implement model evals, monitoring, and drift detection.
Package and deploy models to production systems.
Optimize training and inference performance, cost, and reliability.
Collaborate with data, platform, and product teams.
Mentor engineers and promote ML engineering best practices.

It starts with you - an engineer driven to build resilient, automated infrastructure that enables teams to move fast with confidence. You care about operational excellence, developer experience, and reliability at scale. Youll architect and operate the compute and networking infrastructure that powers our AI platform - from CI/CD pipelines to Kubernetes clusters to observability systems - across cloud and on-prem environments.
If you want to build infrastructure that powers mission-critical AI systems at national scale, join our companys mission - this role is for you.
The Responsibilities
Architect and operate Kubernetes-based infrastructure across AWS and on-prem environments, ensuring high availability, security, and performance.
Design and maintain CI/CD pipelines for application and service deployments with automated testing, security scanning, and rollback capabilities.
Drive infrastructure-as-code practices for compute and networking - building reproducible, auditable, and version-controlled infrastructure.
Own reliability and incident response - establish SLOs, build alerting systems, lead incident resolution, and drive post-incident improvements.
Enable AI-native operations - support agentic deployment pipelines, self-healing infrastructure, and secure sandboxing for model experimentation.
Build and maintain observability systems - metrics, logging, tracing, and dashboards that provide visibility into system health.
Optimize infrastructure cost and performance - right-size resources, implement auto-scaling, and identify efficiency opportunities.
Collaborate with Engineering, Data Platform, Data Engineering, and Security teams to align infrastructure with platform needs.
Shape infrastructure characteristics that support data freshness, correctness, and low-latency pathways for AI training/inference, retrieval, and agentic workflows.
Contribute paved-road tooling - reusable CI/CD patterns for services, IaC modules for compute and networking, and runbooks - that streamline delivery across teams.
Collaborate with Engineering, Data Platform, Data Engineering, Security, Product, AI/ML, Data Science, and Analytics to anticipate and meet cross-functional needs.

Were looking for a Senior Program Manager to own the execution of our Sovereign AI roadmap end-to-end. Youll sit within the Product group and act as the connective bond between Data Science, Engineering, and Product - making sure complex, cross-functional initiatives ship on time and at the quality bar our customers expect.
If you are an unblocker, enjoy making tough tradeoff calls, and drive accountability across the board, your place is with us. Youll manage multiple parallel workstreams across verticals (Security, Health, AML, and more), platform, and AI/ML domains- and youll be the person everyone relies on to know and manage where things stand and what is about to happen next.
The Responsibilities
Own and manage the full lifecycle of Sovereign AI projects from planning through delivery. Track milestones, dependencies, and risks across multiple concurrent workstreams.
Drive cross-functional alignment, and work daily with Data Science, Engineering, Product, and Design teams to ensure same direction. Break down silos and surface early mitigation.
Maintain clear, accurate visibility into project status, blockers, and timelines. Communicate proactively to stakeholders and management.
Identify and solve risks, by own and drive resolution.
Work closely with senior leadership and domain leads to ensure roadmap priorities reflect strategic goals.
Translate execution-level realities into clear decision points - when tradeoffs need to be made, you frame the options and drive alignment.
Interface with internal leadership and external government stakeholders to align on scope, timelines, and priorities. Keep information flowing in both directions.
Continuously refine processes, rituals, and tools to make the team more effective without introducing unnecessary overhead.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company'sAI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Responsibilities
Conduct cutting-edge research in natural language processing and large language models.
Design, train, and optimize large-scale neural network models for advanced applications.
Transition research projects from ideation through deployment and scaling.
Collaborate closely with cross-functional teams, including domain experts, product managers, and engineers, to deliver impactful AI solutions.
Define and contribute to the AI and NLP product roadmap.

we are seeking a Threat Researcher to analyze enterprise environments and strengthen network resilience. This role focuses on researching device configurations, network relationships, and lateral movement opportunities, while developing methods and tools to harden infrastructures against advanced threats.
The ideal candidate will also support PoCs by applying research capabilities to real-world govermental environments and working closely with customers to validate threat scenarios and demonstrate cyber value.
The Responsibilities
Analyze various network devices, configurations, and security products
Implement methods and algorithms to discover network topology, relationships between devices, and potential lateral movement paths
Conduct network security assessments to identify weaknesses in customers' network infrastructure and recommend mitigations to monitor and limit unauthorized access
Develop research tools and frameworks to perform automatic analysis of network devices and security products
Research and analyze network-related cybersecurity threats and trends
Drive threat research efforts in customer and PoC environments to uncover, simulate, and validate real-world attack scenarios, demonstrating cyber value through our company Securitys platform capabilities
Translate technical research findings into actionable insights for customer-specific environments.
Work closely with other internal engineering and AI teams to integrate new capabilities into our platform and guide cross-product architectural decisions
Act as a security subject matter expert for multidisciplinary teams
Produce technical reports and research publications to share findings and methodologies.

This role sits at the centre of execution. Youll support our client executive team, solution architects, support engineers, deployment squad, and training leads - ensuring every post-sale interaction is coordinated, tracked, and elevated to our companys standard of excellence. You will also build systems to monitor collections, renewal timelines, and customer financials.
our companys customer relationships are strategic - we work with national agencies and critical infrastructure operators. Your job is to make sure every delivery is executed with clarity, speed, and rigor.
The Responsibilities
Cross-team operational coordination
Act as the operational right hand to our companys client executives, helping align customer priorities with internal execution.
Drive task and milestone tracking across solution architects, support, deployment, and training - ensuring no handoff is missed.
Build and maintain internal tools and views to visualize the customer journey across multiple workstreams.
Financial and renewal operations
Maintain clear visibility on customer revenue, invoicing, and collections in coordination with finance.
Track contract end-dates, renewal risk, and revenue exposure - building dashboards and alerts for leadership.
Prepare supporting material and ops-readiness for renewal conversations, including usage stats, delivery KPIs, and unmet needs.
Delivery health & issue management
Build and own reporting systems for implementation status, customer activity levels, issue escalations, and open action items.
Coordinate internal response during high-priority escalations: track resolution steps, timelines, and accountability.
Ensure structured follow-ups from deployments: validate remediation adoption, training completion, and customer engagement.
Systematization & documentation
Maintain shared visibility into execution: build dashboards, write playbooks, and track decisions that impact customer success.
Help drive internal alignment on priorities, especially where product, delivery, and customer success intersect.
Own the operational checklist for new deployments and expansions.

We are on an expedition to find Technical Delivery Engineer, someone who is passionate about creating intuitive, out-of-this-world In this role, you will lead end-to-end implementation and deployment projects of our companys platform in customer environments, working hands-on with AI on-prem and hybrid infrastructures.
Youll collaborate closely with Product, Architecture, and R&D teams, while serving as a trusted technical partner for customers and senior stakeholders. From planning and execution to troubleshooting and continuous improvement, you will own the full delivery lifecycle and ensure every deployment is reliable, seamless, and impactful.
The Responsibilities
Lead end-to-end project delivery in close collaboration with Product, Architecture, R&D, and Solutions teams, as well as customer executives and senior stakeholders.
Plan, coordinate, and execute complex on-premises deployment projects.
Take a hands-on role in deploying our companys platform within customer environments.
Serve as the technical escalation point for issues related to product deployment and implementation.
Develop, maintain, and continuously improve project delivery processes and knowledge-sharing practices.
Communicate project status, milestones, risks, and dependencies clearly to internal teams and customer stakeholders, ensuring transparency and alignment throughout the delivery lifecycle.

we are seeking a skilled and adaptable Solution Architect to lead deep technical engagements during both pre-sales and post-sales phases. You will ensure seamless deployment, resolve complex technical issues, and deliver long-term value to customers through our companys AI-powered cybersecurity platform.
This role also includes ownership of lab environments to simulate customer use cases, validate solutions, and support internal testing and demos-making it a key technical bridge between Product, Engineering, and Customer Success.
The Responsibilities
Build and maintain strong relationships with customers, serving as a trusted technical advisor to understand and address their needs, challenges, and goals.
Collaborate with internal teams, including R&D and Product, to align customer feedback with roadmap priorities and platform improvements.
Lead the technical aspects of Proof of Concepts (PoCs) and guide customers through pre-deployment readiness.
Drive post-sales success by resolving complex issues, optimizing deployments, and identifying opportunities to improve security posture.
Deliver technical enablement and training sessions for customer teams to ensure strong adoption and platform fluency.
Stay informed on the latest in cybersecurity, infrastructure, AI, and cloud technologies to continuously elevate customer outcomes.
Lab Environment Ownership: Responsible for designing, maintaining, and automating lab environments that simulate real world customer deployments to test product features, validate integrations, demonstrate the company platform, and support cross-functional testing and customer issue replication.