About Starya
Starya develops AI for complex operations. We connect artificial intelligence, software, and data to transform real business processes with security, reliability, and control.
Our platform, NebulaOS, is the foundation for building, integrating, and operating these solutions. Our work combines engineering close to customers, product development, and a foundation of data, infrastructure, and security.
The challenge
Guide the evolution of the shared NebulaOS platform, connecting data, infrastructure, and security to Product and Client Engineering needs. Turn recurring dependencies into documented capabilities, with defined owners, conditions of use, and maintenance. Develop autonomy within specialties and build joint decisions about capacity, reliability, protection, and cost, connecting technical planning to work observed in operations.
What you will do
- Organize platform priorities around the journeys it serves, recurring failures, and delivery dependencies. Produce a plan covering the problem, alternative, effort, risk, and owner; negotiate sequencing with Product and Client Engineering and revisit commitments when new evidence emerges.
- Define consumption contracts for environments, pipelines, and controls with specialists: how to request, configure, authenticate, observe, and recover each capability. Maintain a catalog, documentation, and adoption criteria, deciding what should be standardized and how to handle exceptions with explicit maintenance ownership.
- Develop Data Engineers, SREs, and Security Engineers through feedback, reviews, and delegation of complete areas of work. Agree on development goals, decision authority, and supporting peers; contribute directly to designs and prototypes that reduce material uncertainty for the team.
- Lead architecture reviews across services, data, and infrastructure, checking access boundaries, isolation between organizations, integration contracts, and recovery. Record alternatives and decisions with technical owners, including how a change will be validated and who will own its evolution.
- Build capacity and cost plans using usage data, forecast loads, and external dependencies. Compare sizing, simplification, and automation; bring effects on latency, data processing, model execution, and teams’ operational effort into prioritization.
- Organize the handover of capabilities into use and maintenance: acceptance criteria, documentation, diagnosis, recovery, and component owners. Follow incidents and changes to turn recurring causes into prioritized improvements, escalating risk decisions and exceptions to the designated authority.
What we look for
- Experience leading platform, data, or infrastructure initiatives, with examples of capabilities adopted by other teams and how their contracts and maintenance were defined.
- Practice developing people and distributing technical decisions, combining feedback, follow-up, and hands-on contributions to problems requiring architecture review or investigation.
- A foundation in systems architecture to discuss networks, identity, persistence, integration, and failure modes; ability to explore decisions in depth with specialists in each discipline.
- Ability to negotiate priorities and dependencies with consuming teams, using impact, risk, cost, and effort to present alternatives and organize delivery commitments.
- Experience evaluating operational, data quality, and protection evidence, turning incidents, limitations, and manual work into investment decisions and verifiable improvement criteria.
Additional experience
- Experience with platforms serving multiple organizations or cloud environments such as AWS, OCI, or equivalents, including access design, isolation, and operation of shared components.
- Experience creating self-service paths for deployment or data, with versioned standards, usage examples, observability, and mechanisms to receive and prioritize consumer needs.
- Participation in decisions connecting AI application cost, capacity, and reliability, including model dependencies, data processing, and enterprise integration constraints.
Your impact
Impact will be tracked through the time and effort needed to make capabilities available, adoption of standardized paths, manual dependencies, recurring failures, and costs relative to usage. The team’s ability to make decisions and maintain its components also matters. Each metric will have a definition and context agreed with platform consumers.
Who you build with
You work with Product on priorities and Client Engineering on conditions for customer delivery. Specialists lead decisions within their disciplines; the Lead coordinates commitments between them. Product Engineering participates in contracts and core changes, while system owners and risk acceptance authorities validate the decisions within their remit.