Senior Generative AI Developer

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.

Key Responsibilities:

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

Qualifications:

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)