דרושים » AI » Senior AI engineer

We are seeking an experienced Generative AI Engineer to join our AI squad. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field.
Key Responsibilities:
GenAI Development & Implementation:
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability
Continuous Learning & Innovation:
Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge
Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment

Were looking for a Senior Data Science who is excited about designing and building production-grade AI systems powered by modern LLMs and machine learning.
This role is ideal for someone who enjoys working at the intersection of AI, engineering, and product, and who is passionate about turning cutting-edge AI capabilities into reliable, scalable systems that solve real customer problems.
Youll work closely with product managers, data scientists, and engineers to design, build, and deploy AI-powered solutions - including LLM pipelines, agents, and intelligent automation systems that power our core products.
This is a hands-on role where youll take ownership of the full lifecycle of AI features - from problem framing and architecture design to deployment, evaluation, and iteration in production.
Responsibilities:
Design and build AI-powered systems that leverage LLMs, embeddings, and modern NLP techniques to transform raw product data into structured, actionable insights
Develop and maintain production-grade AI pipelines including prompt workflows, agents, retrieval systems (RAG), and automated decision processes
Work closely with product and engineering teams to translate business needs into scalable AI solutions
Architect systems that combine LLMs, data pipelines, and traditional ML into robust end-to-end products
Experiment with and integrate new AI tools, models, and frameworks to continuously improve system capabilities and performance
Own the full lifecycle of AI features - from design and prototyping to deployment, monitoring, and iteration
Ensure reliability and performance of AI systems in production, including evaluation frameworks, guardrails, and monitoring
Collaborate across teams to define best practices for AI system design, prompt engineering, and agent orchestration
Collaborate closely with cross-functional team members, effectively communicate complex ideas, share knowledge, and mentor engineers and data scientists to elevate team standards and impact

we are looking for a AI Architect.
Responsibilities:
1. AI Architecture & Technical Leadership
Guide AI architectural direction across Navinas platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.
2. Hands-on Applied Innovation (Core Pillar | ~50%)
Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:
De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering
3. Best Practices & Technical Enablement
Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)
Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.
Responsibilities:
Lead a team of data scientists, data engineers and product analysts
Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation
Drive excellence, code quality, and best development practices
Provide technical direction and hands-on guidance for complex AI systems
Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences
Ensure AI solutions are safe, scalable, observable, and continuously improving
Lead initiatives around product data analysis and experimentation
Analyze user interactions with product features to improve accuracy, UX, and business impact
Partner with product teams to define metrics, dashboards, and experiments that guide product improvements
Design system architectures for AI-enabled applications at scale
Evaluate and select technologies for AI platforms and data pipelines
Guide the development of prompt engineering frameworks and centralized prompt management
Ensure robust monitoring, evaluation, and feedback loops for AI outputs
Translate product and business goals into technical roadmaps and execution plans
Drive alignment between AI capabilities and measurable product outcomes.

You will manage the AI Platform Engineer(s), set the technical standards for the AI Power User group's citizen development program, and serve as the connective tissue between business leadership, platform owners, and development teams. You will shape the multi-year AI architecture roadmap while also rolling up your sleeves to conduct architecture reviews, resolve blockers, and move use cases from concept to production. This is a role for someone who can think big and execute - and who understands that in an enterprise context, the quality of your governance is inseparable from the quality of your architecture.
What You'll Own
Strategy & Architecture
Define and own the enterprise AI integration strategy - identifying opportunities to embed intelligent automation, agentic workflows, predictive analytics, and generative AI capabilities across our core platforms
Develop and maintain reference architectures, design patterns, and the AI architecture decision log that governs how AI models connect to enterprise systems and what they are permitted to do
Consult on enterprise system architecture and implement best practices for the Enterprise Business Systems team to leverage in their day-to-day execution.
Lead Proof-of-Concept initiatives for new AI tools and platform-native AI features, evaluating them against build-vs-buy criteria before recommending adoption
Partner with business stakeholders to translate operational pain points into AI use cases with clear ROI framing and sequencing criteria
Contribute to our enterprise data strategy, ensuring AI initiatives are supported by clean, accessible, and well-governed data pipelines
Integration Architecture & Delivery

Design and own the Workato eMCP layer - the MCP governance model, persona-scoped token framework, workspace isolation strategy, and the single sanctioned action surface through which all AI agents write back to enterprise systems
Define integration patterns and standards for AI model connectivity (Claude, ChatGPT) to Salesforce, NetSuite, HiBob, and Jira - specifying what agents can read, what they can write, through which surfaces, and with what confirmation and audit requirements

In this role you'll design and build features that shape how customers discover products - tailored to their preferences, helping them find exactly what they need, even before they know they need it. We're defining how LLMs integrate into real-time personalization, how noisy behavioral signals become durable customer understanding, and how AI-powered experiences ship reliably at scale. You'll work across multiple technical teams, ship iteratively, and see your work in the hands of customers quickly. This organization values experimentation, moves fast, and gives engineers real ownership over what they build.

We are looking for a Senior Software Development Engineer who leads through technical depth and sound judgment. Someone who owns team-level architecture, provides system-wide design guidance, and brings perspective on both current and future technology choices. You take on customer problems where the technological strategy is not yet defined, and you drive productive discussions to align teams on the best path forward. You dont just deliver high-quality software yourself - you set the standard that others follow. You actively mentor multiple engineers, drive adoption of engineering best practices, and ensure your team has strong operational foundations. You make the team permanently stronger, not dependent on your presence. When the right solution isnt technical - when its a process change, a culture shift, or a staffing decision - you recognize that and act accordingly.

Key job responsibilities
- Own team architecture of personalized recommendation system operating in our scale.
- Lead the design and delivery of cross-teams projects end-to-end, with focus on maintainability, scalability, performance, and reliability.
- Collaborate with Product and Science to define technical roadmap and experiences based on data.
- Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI.
- Define and drive measurement strategies including analytics events and experiment configurations to track business and technical metrics.
- Create clarity from ambiguity and make sound technical decisions in a problem space where established patterns don't apply.
- Drive adoption of engineering best practices through exemplary personal coding practices.
- Proactively simplify existing systems and resolve endemic, root-cause problems.

We are looking for a hands-on, business-minded AI Engineer to join our Data & AI Team.
This role is for someone who has already built and shipped real AI products in a company environment. You will work as an integral part of the Data & AI Team, partnering directly with business stakeholders to identify high-impact opportunities, translate business needs into technical solutions, and build AI products that automate internal processes and create immediate value.
The ideal candidate is a builder. You should be comfortable working with LLMs, AI agents, automation workflows, APIs, data pipelines, data warehouses, and internal company systems. You should also be comfortable taking ownership, asking sharp business questions, and moving ideas from concept to production.
Our Data Team has already built internal AI products at our company. Now we are looking for someone who can help take us to the next level.
What Were Looking For
The right person has built with AI in a real company environment and knows how to turn business needs into practical internal products. They should be comfortable working with stakeholders, understanding how teams operate, and identifying where AI can create meaningful value.
Because this role sits inside the Data & AI Team, they also need to be strong with data. That means working confidently with company data, data warehouses, pipelines, APIs, and the technical building blocks that make AI products reliable and useful.
This role is for someone hands-on, curious, and hungry to build. Someone who can combine AI, data, and business context to help us move faster, automate smarter, and turn ideas into measurable business wins.
What Youll Do
Build end-to-end internal AI products, automations, agents, and workflows that solve real business problems across our company.
Work directly with business stakeholders to understand pain points, define requirements, and turn ideas into scalable AI-driven solutions.
Design, prototype, test, deploy, and maintain production AI products using LLMs, AI agents, APIs, automation frameworks, and internal company data.
Work hands-on with data tools and infrastructure, including Snowflake, ETLs, data pipelines, APIs, AI tools, and internal servers.
Identify high-impact manual processes and turn them into automated AI-driven business wins.
Evaluate new AI tools, frameworks, and agentic workflows, and apply them where they can improve productivity, decision-making, or business operations.
Help shape internal AI development best practices around reliability, usability, security, documentation, maintainability, and production readiness.

We are looking for a Hands-On Team Lead - Agentic Engineering to lead, build, and actively contribute to a new team focused on applying AI agents, and intelligent workflows to improve business processes across the organization.
This role is both a technical leadership role and a hands-on engineering role. The successful candidate will manage the first Agentic Engineer, help grow the team, and personally contribute to the design, development, integration, and deployment of agentic AI solutions.
The ideal candidate is someone who can lead from the front: writing code, designing architectures, building prototypes, reviewing technical work, solving complex implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI-driven solutions.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
Governance, Reliability & Security
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners and IS teams to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations.

We are seeking a Senior AI Engineer to join a talented and fast-moving AI Engineering team. We're the central hub for AI across, driving innovation and putting AI to work for every team and product in the company.
AI already plays a foundational role in how we operate. It lets us ship features quickly and at scale, equips non-technical team members with tools that boost their productivity, and underpins much of the innovation happening across the company today.
If this kind of environment excites you - and if you believe great engineering means crafting the most effective and elegant solution within real-world constraints - we'd love to hear from you.
What You'll Be Doing:
Design, build, and maintain reusable AI capabilities - spanning models, tools, APIs, and platforms that support both internal operations and customer-facing products.
Develop and maintain our internal MCP server, giving AI agents easy and secure access to our extensive data stores.
Create and implement rigorous evaluation frameworks and AI guardrails to protect our value and ensure model reliability.
Cultivate deep expertise and establish sustainable AI engineering practices across the organization.
Champion AI readiness and track adoption company-wide to build lasting impact.
Build and optimize RAG (Retrieval-Augmented Generation) systems.
Own projects end to end - from gathering requirements from non-technical stakeholders through development, deployment, and ongoing operation.
Serve as a consultant and advocate for AI engineering, guiding other teams in leveraging the platforms and tools you create.
Collaborate with teams throughout to accelerate AI adoption and productization.

We are looking for engineers who are excited about building real-world AI systems in production, not just experimenting with models, but designing scalable applications, integrating intelligent agents into complex products, and solving challenging engineering problems with direct customer impact.
Key Responsibilities
Design, develop, and maintain AI-powered applications, agents, and backend systems
Build intelligent workflows and agentic systems integrated into our company networking and security products
Develop scalable APIs, services, and infrastructure supporting GenAI applications in production
Integrate LLMs, RAG pipelines, vector databases, and orchestration frameworks into robust production systems
Collaborate closely with AI researchers, software engineers, infrastructure teams, and product groups to deliver end-to-end AI solutions
Improve scalability, reliability, observability, and operational excellence of AI systems
Explore and adopt modern AI engineering methodologies, frameworks, and tooling
Participate in architectural and technical decisions shaping the future of AI across our company products.