We’re a software house passionate about building solutions that change how our clients use data and artificial intelligence. For over 9 years, we’ve been developing innovative AI-driven products such as InfraSenses and SolarSpy — not just using ready-made tools, but also building machine learning models from scratch.We’re looking for an experienced Senior Generative AI Developer to join our Client’s AI engineering team in the insurance industry, building enterprise-grade Generative AI and LLM solutions that are redefining intelligent insurance platforms. You’ll design, deploy, and optimize multi-cloud GenAI systems, leading innovation in LLM orchestration, multimodal architectures, and scalable AI pipelines. This is a hands-on technical leadership role, combining development with mentoring and ensuring solutions meet business, performance, and ethical AI standards. Work with cutting-edge technologies like Azure OpenAI, GCP Vertex AI, AWS Bedrock, PyTorch, and LangChain, and help shape the AI strategy and best practices for global-scale projects in the insurance domain.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.

What We’re Looking For: 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 We Offer: The opportunity to build advanced Generative AI and LLM solutions for a leading insurance industry client. Work with cutting-edge AI technologies (Azure OpenAI, GCP Vertex AI, AWS Bedrock, PyTorch, LangChain) on global-scale projects. Professional growth and mentorship from top-tier AI/ML experts in an international environment. A training budget to support your technical and professional development Private medical care and co-financing of a sports card Flexible working hours and the option to work fully remotely