We are seeking a Technical Manager – Applied AI Operations to lead the operational delivery of AI/ML solutions, ensuring reliable, scalable, and efficient support for production AI systems. This role involves managing client engagements, collaborating with architecture and DevOps teams, and driving innovations in AI/ML operations—especially in the context of LLM-based solutions.
- AI Model Operations Management Oversee operational support and performance for deployed AI models (eg, GPT, Claude, BERT) in live production environments
- Platform & Architecture Support Guide the use of retrieval-augmented generation (RAG) architectures, vector databases (FAISS, Pinecone), and orchestration frameworks (LangChain, LlamaIndex)
- AI Monitoring & Observability Implement AI monitoring tools and observability solutions (eg, Arize, Evidently) to ensure accuracy, latency, drift detection, and model health
- Client Management Act as the technical point of contact for client-facing delivery of AI/ML services, ensuring satisfaction, uptime, and ongoing optimization
- Cross-Functional Leadership Collaborate with solution architects, DevOps engineers, and AI/ML teams to manage infrastructure, CI/CD pipelines, and compliance across deployments
- Accelerator Development Drive the development of operational accelerators and reusable components to standardize and optimize LLM/AI model deployments
- Automation & Efficiency Identify and implement automation opportunities across AI workflows and support functions to improve reliability and reduce manual interventions
- Experience:6+ years in technology management, including 2+ years managing production AI/ML systems and teams
- AI/ML Expertise:Strong working knowledge of large language models, vector databases, and RAG-based architectures
- MLOps Skills:Familiarity with MLOps best practices, pipelines, containerization (Docker/Kubernetes), and cloud-native AI tooling (Azure OpenAI, AWS Bedrock, GCP Vertex AI)
- Tool Proficiency:Hands-on with LangChain, LlamaIndex, Arize, Evidently, MLFlow, or similar operational tools
- Leadership:Proven ability to manage multidisciplinary teams, deliver client-facing projects, and balance priorities under deadlines
- Communication:Strong stakeholder communication skills with the ability to translate complex AI operations into business value
