We’re looking for a Senior Generative AI Developer to lead the design and deployment of enterprise-grade GenAI systems. This is a hands-on individual contributor role with opportunities to provide technical guidance to junior developers. You’ll drive innovation in LLM orchestration, multimodal architectures, and scalable AI/ML pipelines—owning the full lifecycle from research to production while ensuring alignment with business goals and ethical AI standards.
1.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
2. Cloud-Native AI Development
•Build multi-cloud GenAI platforms (Azure OpenAI, GCP Vertex AI, AWS Bedrock) with unified MLOps
•Implement enterprise-grade security: VPC peering, private endpoints, data residency compliance
3. Innovation & Strategy
•Pioneer GenAI use cases: agentic workflows, synthetic data generation, real-time fine-tuning
•Establish AI governance frameworks: model cards, drift monitoring, red-teaming protocols
4. Cross-Functional Impact
•Collaborate with leadership to define AI roadmaps and ROI metrics (e.g., cost savings via automation)
•Mentor junior engineers and promote GenAI best practices across the organization
Education:
Bachelor’s or Master’s in Computer Science, AI, or equivalent 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:
•Delivered production-grade GenAI systems (e.g., 10k+ QPS chatbots, GitHub Copilot-scale autocomplete)
•Advanced prompt engineering: self-critique chains, LLM cascades, guardrail-driven generation
Must-Have Experience:
•Cloud AI Development:
•Azure: Azure OpenAI, MLOps Pipelines, Cognitive Search
•GCP: Vertex AI LLM Evaluation, Gemini Multimodal, TPU v5 Pods
•High-Impact Projects:
•Automation initiatives with measurable cost savings
•RAG systems with hybrid search (vector + lexical) and dynamic data hydration
•AI compliance leadership in regulated industries (e.g., healthcare, finance)
Preferred Qualifications:
•Certifications:
•Microsoft Certified: Azure AI Engineer Associate
•Google Cloud Professional Machine Learning Engineer
•Deployment Experience:
•Hybrid/multi-cloud GenAI setups (e.g., training on GCP TPUs, serving via Azure endpoints)
Imagine working for an organization that truly believes in a set of values which drive its performance, define its culture and help it grow. Imagine that in the center of it all is a team of individuals united in creating a diverse, unique workplace and business experience.
As an industry-focused managed services company, Xceedance partners with insurers, reinsurers and brokers worldwide. Clients rely on us to launch new products, drive operations, implement cutting-edge technology and deliver advanced analytics capabilities and process optimization.
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