Senior Applied AI Engineer (Paradox)

We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

As a Senior Applied AI Engineer, you will lead the bridge between cutting-edge AI capabilities and production-grade software. You will design, build, and optimize the intelligent systems, agentic workflows, and LLM-driven architectures that power Paradox’s conversational products.

Also, you will combine software engineering rigour with state-of-the-art Generative AI techniques - optimizing for conversational quality metrics, latency, and system reliability in high-scale production environments, serving millions of users. We are looking for an engineer who is hungry for AI innovation, eager to pioneer new generative capabilities, and passionate about shipping impactful AI solutions.

In this role, you will:

• Design & Scale AI Systems: Architect and deploy high-performance LLM orchestration systems, agentic workflows, retrieval-augmented generation (RAG) pipelines, and AI microservices.
• Bridge AI Research & Production: Transform frontier LLM research, foundation models, and generative techniques into robust, production-ready features with high availability and low latency.
• LLM Evaluation & Guardrails: Design and implement automated LLM evaluation (evals) frameworks, benchmark suites, and guardrail policies to continuously measure accuracy, reduce hallucinations, and ensure safety across product flows.
• Optimize Performance & Cost: Lead latency, throughput, and token-cost optimization strategies across commercial APIs and open-source models.
• Set AI Engineering Standards: Elevate software craftsmanship across the team through architectural reviews, code quality, and LLMOps best practices, utilizing the latest AI tools.
• Drive Product Innovation: Collaborate closely with product and engineering teams to translate complex human resource and conversational challenges into intelligent software solutions.

• Applied Generative AI: Proven track record of shipping complex LLM systems to production (e.g., Multi-agent architectures, RAG systems, tool/function calling, complex dialogue managers) coupled with a passion for continuous AI innovation.
• 5+ years of hands-on software development experience, focusing on building complex, distributed systems.
• System Architecture & Cloud: Strong system design skills in cloud-native environments (AWS/GCP), containerization, and modern CI/CD automation.
• Engineering Quality for AI: Deep understanding of testing non-deterministic AI systems (eval-driven development, deterministic regression testing, automated benchmarking).
• Technical Leadership: Proven experience leading architectural designs, driving cross-functional alignment, and mentoring engineers in AI engineering principles.
• Fluent English: High proficiency in both written and verbal communication.
• Work Authorization: Authorization to work in Israel.

Preferred Qualifications:

• Python Expertise: Deep proficiency in Python and modern backend framework development, with strong API design and asynchronous programming skills.
• Vector Search & AI Infrastructure: Hands-on experience with Vector Databases (e.g., Pinecone, Qdrant, Milvus, pgvector) and modern orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen/CrewAI).
• Model Customization & Fine-Tuning: Practical experience with model fine-tuning techniques (e.g., LoRA, QLoRA, SFT, DPO/RLHF) and dataset curation.
• LLMOps & Observability: Hands-on experience with LLM tracing and observability stacks (e.g., LangSmith, Phoenix, Arize, Weights & Biases).
• Inference & Serving: Familiarity with LLM serving engines and frameworks (e.g., vLLM, TensorRT-LLM, Ollama).
• Domain Experience: Background in Conversational AI, Dialogue Management, or Recruitment/HR tech automation.
• Data Science/ML Foundation: Formal background or practical grounding in NLP, Machine Learning, or Data Engineering.

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