Own the cloud-native AWS architecture for a new MCP project and lead a technical team of engineers and AI specialists. Act as the primary technical point of contact for the client while remaining hands-on with coding and PR reviews.
Own the full-cycle recruiting process for senior technical roles, including sourcing, screening, and pipeline management in Airtable. Partner with technical leads to design scoring rubrics and manage the flow from assessment to client presentation.
Own the security posture of the Model Context Protocol (MCP) infrastructure, focusing on authentication, secrets management, and AI guardrails. Additionally, manage and remediate the broader application security backlog for the client's software systems.
Design and implement the backend infrastructure for Model Context Protocol (MCP) server components to enable tool-use and agent orchestration. Collaborate with a technical lead to integrate these AI layers into an existing Java and SQL Server production stack.
Maintain and optimize agentic AI infrastructure using LangChain and MCP protocol. Own the deployment pipelines, observability, and production stability for LLM-based systems.
Design and implement advanced Deep Learning models and Transformer architectures while ensuring reproducibility through MLOps. Build and secure high-performance APIs to serve models in production environments within fast-paced weekly sprints.
Lead the end-to-end vision and delivery of multiple AI products for non-technical mid-market companies. Partner with the CEO to map internal processes and convert high-level uncertainty into concrete product roadmaps.
The specialist will design and implement state-of-the-art Deep Learning models, particularly Transformers, while leading the standardization of reproducible ML environments using MLflow and DVC. They will also be responsible for building, profiling, and securing high-performance APIs to serve these models in production environments within fast-paced 1-week sprints.
The Product Manager will be responsible for driving the roadmap and execution across two to three distinct products simultaneously, ensuring seamless delivery from initial research through final user testing. This involves leading ideation, maintaining high execution standards through tight project management, and collaborating cross-functionally with stakeholders.
The role involves architecting custom AI adoption frameworks and driving the operationalization of AI across targeting, content, and revenue analytics in partnership with product and engineering teams. Additionally, the individual will manage AI governance, safety, and ethical execution while acting as C-Suite advisory.
