דרושים » AI » Senior Data & AI Engineer

CodeValue is a leading software development and technology consulting company, partnering with startups and enterprise organizations to deliver innovative, production-grade solutions across cloud, AI, cybersecurity, data, and digital platforms. We are expanding our AI engineering capabilities and looking for a Tech Lead / Principal AI Engineer to serve as our professional authority and lead the architecture, design, and implementation of advanced Generative AI, LLM, and Agentic systems that solve real-world engineering and operational challenges. This role combines hands-on software engineering, advanced LLM systems design, MLOps, and platform thinking. You will work closely with engineering teams, architects, and customers to build scalable, production-grade AI solutions that move beyond experimentation into reliable, cloud-native production environments.

In this role on our AI team, you'll focus on agentic workflow automation. You'll design, build, and deploy reliable AI agents that automate complex HR, payroll, and payment workflows, handling decision-making, document intelligence, and complex tasks that typically require human judgment.

What You'll Do:
Design and build agent-based systems that automate document processing, business insights, and complex enterprise workflows.
Build observability, evaluation, and feedback loops for agent behavior to improve reliability, accuracy, and trust in production.
Own the technical architecture and engineering standards for agentic systems.
Build or manage data pipelines to process large volumes of documents and unstructured data.
Collaborate with domain experts to identify high-value automation targets and deliver end-to-end solutions.
Stay current on agent frameworks, LLM capabilities and limitations, and apply emerging patterns pragmatically in production.

we are looking for a Senior Data Engineer to join our Data Platform team. We are seeking a hands-on individual with experience in building and scaling modern data infrastructure, passionate about exploring AI technologies and applying them to enhance and evolve our data systems. This role is ideal for someone focused on data systems, performance, automation, and reliability, who will design, build, and maintain core components of our data pipelines, storage, monitoring, and observability stack, with a strong focus on improving workflows and system capabilities, while embracing the Shift4 way.

Responsibilities:

Build and maintain scalable, reliable, and high-performance data infrastructure across cloud and on-prem environments
Partner with engineering, analytics, and observability teams to support data flow from ingestion to consumption
Develop infrastructure as code and automation tools to improve deployment, monitoring, and recovery
Help troubleshoot performance bottlenecks and reliability issues in large-scale data pipelines
Implement data quality processes aligned with security standards to ensure accuracy, consistency, and compliance with financial regulations and PCI requirements.
Continuously improve the performance and efficiency of the data platform with proactive tuning and benchmarking
Proactively explore and apply AI tools to enhance efficiency across the data engineering lifecycle, while improving accessibility and usability of data solutions for teams across the organization

Fire-Arc is an innovative, data-oriented, high-tech company that owns, develops, and publishes multi-platform digital Assets. All our products and content coordinate together to create unique monetization solutions and advanced revenue streams for digital properties. We are expanding our teams and are focused on adding like-minded, result-oriented, and high-achieving talents. We’re looking for a Mid-Level Client Developer with strong leadership capabilities, extensive experience building Windows desktop applications , and a passion for mentoring others and solving complex problems.
Impact and Responsibilities
* Lead the design and development of Windows desktop applications using technologies mostly C# (.NET) WPF
* Drive high-quality integrations with AWS services like S3, Lambda (serverless), EC2, DynamoDB and RDS
* Use AI-powered development tools and IDEs (such as GitHub Copilot, Cursor, and similar assistants) as part of the daily workflow to improve development speed, code quality, and problem-solving
* Design, build, and maintain backend services that support and seamlessly integrate with Windows desktop client applications.
* Apply practical experience with Generative AI tools to increase productivity while maintaining strong engineering standards and critical thinking.
* Proactively identify technical and architectural challenges, and craft scalable, secure, and user-centric solutions
* Oversee and enhance application installation, deployment, and update processes with a focus on security and user experience
* Foster a collaborative, respectful work environment , supporting team members and driving alignment with cross-functional teams
* Participate in code reviews and contribute to a culture of quality and shared knowledge
* Continuously monitor and optimize application performance, security, and scalability
* Stay up-to-date with industry trends and recommend new tools, techniques, or improvements to enhance team effectiveness

Brand:
FireArc

A hands-on engineering role focused on building production-grade AI/ML systems and the automation infrastructure that supports them - driving AI adoption into developer workflows, internal tooling, and domain-specific applications across the organization.

As a member of the AI Infrastructure & Applications team, you will lead the design, development, and production deployment of AI/ML-powered systems alongside the automation infrastructure and developer platforms that support them.
You will architect intelligent, scalable solutions used across the organization - driving AI adoption into developer and automation workflows, internal tooling, and domain-specific applications - while also building and maintaining the automation frameworks and infrastructure those systems depend on.
The systems you build are expected to be production-grade, reliable, observable, and continuously improving.

Responsibilities
Architect and ship end-to-end AI-powered applications and pipelines, from prototype to production.
Build agentic systems, RAG pipelines, and tool-use patterns that integrate LLMs into real workflows.
Define and own AI quality metrics (accuracy, groundedness, hallucination rate, task completion) and integrate them into CI/CD release gates.
Design evaluation frameworks for non-deterministic systems: offline evals, human-in-the-loop review, and automated regression suites.
Harness AI/LLMs to extend and enhance existing automation infrastructure, improving system performance and operational efficiency.
Build scalable automation frameworks, APIs, and tooling used across the organization.
Collaborate with engineering, CI, and domain teams to address automation needs across hardware, software, and cloud.
Distill requirements from a large, diverse user base into generic, reusable, maintainable solutions.
Implement monitoring, drift detection, and structured feedback pipelines for continuous improvement.
Apply rigorous engineering discipline - test design, release criteria, rollback strategies - to AI-native deployments.
Partner with product, design, and domain experts to define use cases, acceptance criteria, and rollout plans.

We are looking for a Principal Software Engineer at the intersection of AI/ML and security. You will drive the architecture and delivery of autonomous agentic experiences that investigate, triage, remediate, and harden customer environments using LLMs, knowledge graphs, and the Security Graph (MSG).

This is a high-impact IC role reporting to the Exposure Management engineering leadership. You will influence strategy, mentor senior engineers, and ship production systems used by the largest enterprises in the world.

Responsibilities

Architect & Build Agentic Security Experiences
Design and implement Blue (investigate/triage), Green (remediate/harden), and Red (attack simulation) agents operating across customer environments.
Define agent architecture: planning, tool use (MCP skills), memory, context retrieval, and human-in-the-loop controls.
Build orchestration over the Security Graph, correlating exposure signals across cloud, device, identity, data, and AI.

Drive AI-Native Platform Design
Architect skill, knowledge, context, and memory layers for agentic security systems.
Design MCP-based skill interfaces for customization and extensibility.
Define how LLMs interact safely and accurately with structured security data (vulnerabilities, misconfigurations, attack paths, graph relationships).

Shape AI-for-Security Strategy
Partner with PMs and domain leads to define where AI autonomy vs. human involvement is needed.
Evaluate and integrate foundation models (Azure OpenAI, fine-tuned models) for tasks such as risk scoring, remediation planning, and blast radius analysis.
Stay ahead of industry solutions (Wiz AI-APP, CrowdStrike Charlotte AI, Palo Alto XSIAM).

Technical Leadership & Influence
Set technical direction across multiple teams (20-30 engineers).
Drive architecture decisions, design reviews, and engineering excellence.
Mentor senior engineers (L63-L65) and grow the AI-for-security discipline.
Represent the team across us (Security Copilot, MSG, Azure AI, Research).

In this role on our AI team, you'll build and scale core AI systems that power our products. You'll work across agentic document intelligence, autonomous agents, compliance AI, and ML-powered insights, prototyping quickly, building robust evaluations, and shipping production-grade AI with real business impact.

What You'll Do:
Build and ship AI/ML solutions using LLMs, agents, RAG, and document understanding models, alongside classic ML.
Prototype quickly, validate feasibility, and turn strong POCs into production systems.
Evaluate models and architectures, apply testing and guardrails to improve agent and service reliability.
Research and apply emerging techniques: multimodal/document AI, agentic frameworks, synthetic data generation, and new architectural approaches.
Work cross-functionally with product, R&D, and compliance teams to deliver end-to-end solutions.
Contribute to scalable, secure architecture and engineering best practices for AI delivery.

we are an innovative, data -oriented, high-tech company that owns, develops, and publishes multi-platform digital Assets. All our products and content coordinate together to create unique monetization solutions and advanced revenue streams for digital properties. We are expanding our teams and are focused on adding like-minded, result-oriented, and high-achieving talents.
Impact and Responsibilities
* Design, implement, and maintain scalable, secure, and reliable cloud infrastructure on AWS (3+ years of experience required) and GCP (preferred).
* Build and maintain CI/CD pipelines to automate application deployment and infrastructure updates.
* Demonstrate hands-on experience using Generative AI tools (e.g., GitHub Copilot, ChatGPT, Cursor, or similar) to accelerate scripting, infrastructure automation, CI/CD configuration, and operational troubleshooting.
* Automate infrastructure provisioning and management using Infrastructure-as-Code (IaC) tools, with Terraform experience being a must.
* Automate infrastructure provisioning and management with Ansible experience being a must.
* Collaborate with development teams to optimize application performance and reliability.
* Troubleshoot and resolve system, application, and network issues to ensure high availability and reliability.
* Ensure the compliance of our infrastructure with security best practices and standards.
* Leverage advanced networking and proxy configuration expertise to design robust and secure systems.
* Continuously research, evaluate, and implement new technologies to enhance infrastructure efficiency and cost-effectiveness.

we are looking for a Mobile SDK Engineer.
What youll do:
Develop and maintain mobile SDK features used by developers worldwide
Design and implement reliable and performant SDK components across multiple mobile platforms and operating system versions
Take ownership of end-to-end quality, including design, implementation, testing, and production reliability
Debug and resolve complex issues across different devices, OS versions, and runtime environments
Improve SDK performance, stability, and reliability at scale
Develop and maintain SDK wrappers and integrations for cross-platform frameworks such as Unity, React Native, Flutter, and other mobile environments
Work with modern AI-driven engineering tools, automation systems, and internal developer platforms
Collaborate with engineers across mobile, backend, frontend, and platform teams
Participate in code reviews and contribute to engineering best practices

Were looking for a Data Engineer who wants to own the full pipeline: from raw event ingestion through distributed processing and into the serving layer that powers our clients dashboards and APIs. This isnt internal tooling - youll be building the actual product surface that advertisers and marketers rely on to understand whats working on the web.
As AI reshapes how data is processed, queried, and served, youll also have the opportunity to integrate AI and LLM-based capabilities into our data workflows - from intelligent data validation and anomaly detection to AI-powered analytics interfaces that make our platform smarter for clients.
What youll do:
Build & Own End-to-End Pipelines: Design, build, and optimize data pipelines that process billions of web events (sessions, in-app events, conversions) with strict freshness and accuracy SLAs. Youll work across the entire attribution data stack - from ingestion and distributed processing through to the serving layer.
Ensure Data Integrity: Own the correctness of complex attribution logic - deduplication, organic vs. non-organic classification, primary attribution resolution, and cross-platform user stitching across massive, partitioned datasets.
Performance Engineering: Optimize scalable distributed processes to meet strict client SLAs. Tune jobs, queries, and pipeline scheduling for maximum throughput and minimum latency.
Ship Client-Facing Features: Partner with Product, R&D, and client-facing teams to turn raw web signals into production-grade, queryable data products that advertisers interact with directly.
Leverage AI in Data Workflows: Explore and integrate AI/ML capabilities into the data platform - from automated data-quality checks and anomaly detection to LLM-powered analytics tools that enhance how clients interact with their data.