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abra Professional Services is seeking a Senior Full Stack Developer to join a leading cloud-based SaaS product team. In this role, you will develop end-to-end features, design scalable backend services, and contribute to architecture, performance, and code quality within a modern R&D environment. Key Responsibilities:
* Develop scalable components in a multi-tenant SaaS platform
* Build high-performance backend services using Node.js and TypeScript
* Design and manage PostgreSQL databases
* Write unit and integration tests and support CI/CD processes
* Collaborate closely with Product, backend, and QA teams

It starts with you - a technical leader whos passionate about database systems and growing high-performing teams. You care about query performance, uptime, data durability, and operational excellence. Youll lead the Datastores team in operating, tuning, and scaling 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 lead a team that keeps the database engines running for mission-critical AI systems, join our companys mission - this role is for you.
The Responsibilities
Lead and grow the Datastores team - hiring, mentoring, and developing engineers while fostering a culture of operational excellence.
Own database reliability and availability - ensuring systems meet demanding SLAs for government and national-scale customers.
Drive performance tuning and optimization - query analysis, index strategies, configuration tuning, and resource optimization across all database engines.
Establish operational practices - backup/recovery procedures, disaster recovery, replication strategies, and failover automation.
Plan and execute capacity management - monitoring growth, forecasting needs, and scaling databases ahead of demand.
Lead incident response for database issues - troubleshooting, resolution, and post-incident improvements.
Enable new capabilities - evaluating, deploying, and operating new database technologies including vector databases for AI workloads.
Partner with Data Platform, Data Engineering, Engineering, and Security teams to align database operations with platform needs.
Define and uphold database SLAs that support retrieval paths, feature stores, and embedding durability; coordinate on schema evolution, partitioning, and safe replay/backfills.
Integrate with catalog and lineage systems - surfacing ownership, change history, and impact analysis for critical datasets and collections.
Collaborate with Data Platform, Data Engineering, Engineering, Security, Product, AI/ML, Data Science, and Analytics to prioritize performance, durability, and evolution of data stores across workloads.

It starts with you - an AI Engineering Team Lead responsible for leading a team building production-grade agentic systems. This role combines hands-on technical leadership with people management, ownership of architecture, delivery, and quality across agents, MCP tools, agentic workflows, RAG systems, and 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
Lead and mentor a team of AI Engineers building agentic systems and MCP tools.
Own technical direction for agent architectures, workflows, and LLM evals.
Review designs and code; ensure production readiness, reliability, and security.
Drive adoption of frameworks such as LangChain, LangGraph, or equivalent.
Set standards for RAG pipelines, vector databases, and retrieval quality.
Partner with product and platform teams on roadmap, scope, and delivery.
Balance hands-on contribution with people management and execution.
Build a culture of strong engineering practices, measurement, and iteration.

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.

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.

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 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.

We are looking for a Technical Presale Engineer with a strong technical orientation in cyber security and networking.
The ideal candidate has 2-4 years of customer-facing experience (e.g., presales, solutionarchitects, technical account managers, training, or consulting), and a willingness to travel.
The role is ideal for people who combine strong technical knowledge with an energetic attitude and the ability to build strong client relationships.
The Responsibilities
We are looking for a Technical Presale Engineer with a strong technical orientation in
cyber security and networking. The ideal candidate has 2-4 years of customer-facing experience (e.g., presales, solutionarchitects, technical account managers, training, or consulting), and a willingness to travel.
The role is ideal for people who combine strong technical knowledge with an energetic attitude and the ability to build strong client relationships.
You will help execute technical presales processes and contribute as a trusted client advisor, ensuring successful solution delivery and long-term customer satisfaction.
We work in a high-paced environment, with frequently changing priorities. Hence a high degree of flexibility and adaptability is required.

Were on the lookout for a driven and experienced hands-on Engineering Team Leader to lead a group of engineers building the AI application foundation behind our next-generation cyber-AI product.
This team owns the core backend and frontend infrastructure that powers all user-facing applications - as well as the agentic and conversational frameworks that bring intelligence and automation into the experience.
As a hands-on leader, youll guide a talented team of engineers in designing and evolving the systems that enable every other Engineering group to create fast, scalable, and intelligent apps on top of our platform.
The Responsibilities
Lead a multidisciplinary team responsible for backend services, frontend frameworks, and AI agent infrastructure - the technical bedrock of our product experience.
Mentor engineers, grow the team, and foster a culture of technical excellence and innovation.
Design and build robust frameworks and systems that power all customer-facing applications.
Develop the agentic and conversational architecture enabling LLM-powered user interactions and intelligent workflows.
Collaborate with AI research, data, and product teams to seamlessly integrate AI-driven capabilities into production systems.
Define and drive the technical roadmap, ensuring scalability, developer productivity, and rapid iteration.