We are looking for a Specialist who will lead the design and deployment of enterprise-grade generative AI systems, driving innovation in LLM orchestration, multimodal architectures, and scalable AI/ML pipelines. Own the full lifecycle from research to production, ensuring alignment with business objectives and ethical AI standards. This will be a hands-on individual contributor role as well as providing technical guidance to junior developers.
Key Responsibilities
Technical Leadership
Architect multi-LLM systems (e.g., Mixture-of-Experts, LLM routing) for cost-performance optimization.
Design GPU/TPU-optimized training pipelines (FSDP, DeepSpeed) for billion-parameter models.
Cloud-Native AI Development
Build multi-cloud GenAI platforms (Azure OpenAI + GCP Vertex AI + AWS Bedrock) with unified MLOps.
Implement enterprise security: VPC peering, private model endpoints, and data residency compliance.
Innovation & Strategy
Pioneer GenAI use cases: Agentic workflows, AI-driven synthetic data generation, real-time fine-tuning.
Establish AI governance frameworks: Model cards, drift monitoring, and red-teaming protocols.
Cross-Functional Impact
Partner with leadership to define AI roadmaps and ROI metrics (e.g., $ saved via AI-driven automation).
Mentor junior engineers and evangelize GenAI best practices across the organization.
Qualifications
Education: Bachelors/Masters in CS/AI or equivalent industry experience (5+ years in ML, 2+ in GenAI).
Technical Mastery:
Languages: Python.
Frameworks: Expert-level PyTorch, TensorFlow Extended (TFX), ONNX Runtime.
Cloud: Certified in Azure AI Engineer Expert and/or GCP Professional ML Engineer.
GenAI Expertise:
Shipped production GenAI systems (e.g., 10k+ QPS chatbots, code autocomplete at GitHub Copilot scale).
Advanced prompt/response engineering: Self-critique chains, LLM cascades, guardrail-driven generation.
Must-Have Experience
Cloud AI experience:
Azure: Designed solutions with Azure OpenAI, MLOps Pipelines, and Cognitive Search.
GCP: Scaled Vertex AI LLM Evaluation, Gemini Multimodal, and TPU v5 Pods.
High-Impact Projects:
Automation projects to reduce significant $$ costs.
Built RAG systems with hybrid search (vector + lexical) and dynamic data hydration.
Led AI compliance for regulated industries (healthcare, finance).
Preferred Qualifications Additions
Certifications:
Azure: Microsoft Certified: Azure AI Engineer Associate.
GCP: Google Cloud Professional Machine Learning Engineer.
Experience with hybrid/multi-cloud GenAI deployments (e.g., training on GCP TPUs, serving via Azure endpoints).
What you can expect from us:
Unique professional and personal development at one of the pioneer companies in professional insurance support.
Ongoing professional training – to onboard you for a good start and your further professional development.
Your own growth training budget - use internal and external development opportunities and take advantage of your own budget.
LUXMED medical cover for you with full dental care, oncological preventive program and additional mental health support with helpline & individual sessions with a therapist.
Flexible work hours (we start between 7:00 and 10:30 am).
8-hour work time with a lunch break already included - spend the rest of the day doing what is important to you as intended in the #2h4Family program.
Private life insurance - 80% of the premium is covered by an employer.
Employee referral program - we appreciate you recommending your friends to join us.
Additional days off - to celebrate your birthday, moreover, if you want to do a volunteering work, feel free to do so with some extra days off.
Integration events - monthly delicious breakfasts, movie nights, board game nights, outdoor events.
Lively and modern office in the City Centre with parking space for employees.
A supportive and friendly atmosphere created by passionate people.
*depending on the type of contract
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