Note: The job is a remote job and is open to candidates in USA. Invoca is an AI-powered revenue execution platform that focuses on transforming customer interactions into profitable growth. They are seeking a Staff AI Platform Engineer to build the core platform for AI development, emphasizing the creation of reusable systems and interfaces that support product teams in developing AI capabilities efficiently and reliably.
Responsibilities
- Build the AI platform foundations: Design and maintain the core APIs, SDKs, libraries, and services that standardize how teams at Invoca build AI and agentic capabilities
- Create reusable agentic platform primitives: Build the platform components that product teams can assemble into real applications, such as orchestration building blocks, tool interfaces, workflow contracts, context-handling systems, and retrieval primitives
- Own platform-level evaluation infrastructure: Build the shared evaluation framework that enables teams to test AI systems consistently and at scale. This includes CI/CD integration, dataset and experiment workflows, scoring pipelines, and support for offline and online evaluation
- Standardize orchestration and interoperability: Help define the contracts, schemas, and interfaces that allow tools, runtimes, and services to work together cleanly. This includes platform patterns for MCP-style interoperability, tool discovery, and agent-to-agent or agent-to-system interactions
- Build for production scale and reliability: Design and improve the serving, routing, and control layers that sit between applications and model providers. You will help ensure low latency, high availability, cost efficiency, and strong production behavior.Drive observability and governance: Build and enforce the platform capabilities that make AI systems measurable, debuggable, and governable in production, including tracing, auditing, policy enforcement, and operational standards.Improve developer experience and platform adoption: Treat engineers and product teams as customers. Create tools, templates, documentation, and reference implementations that make the platform easy to adopt and hard to misuse
- Shape technical direction: As a staff engineer, you will influence architecture, standards, and long-term technical strategy for AI Platform. You will identify repeated patterns across teams and convert them into reusable platform solutions
- Architect the AI platform foundations: Design and evolve the core libraries, SDKs, APIs, and shared services that standardize how teams build agentic and GenAI-powered products at Invoca
- Build reusable agentic and retrieval primitives: Create modular platform components for orchestration, retrieval, tool execution, workflow composition, adoption of latest protocols and standards, and A2A/MCP-compatible interoperability that product teams can use to build production-grade AI systems
- Own the evaluation platform: Build the shared evaluation infrastructure that enables teams to measure and improve AI quality through datasets, scoring pipelines, experiment workflows, and CI/CD-integrated offline and online evaluations
- Standardize context engineering: Develop the systems and tooling for prompt management, context versioning, templating, testing, and governance so teams can iterate safely and consistently on AI applications
- Engineer for scale, reliability, and governance: Build/Establish the serving, routing, and control layers between applications and model providers, ensuring strong production performance, cost efficiency, policy enforcement, and operational resilience
- Drive technical strategy and platform adoption: Partner with product and engineering leaders to turn recurring architectural needs into shared standards, reference implementations, and developer-friendly golden paths that accelerate delivery across the organization
Skills
- 7+ years of professional experience in Platform engineering in AI/ML disciplines, with a strong focus on building shared infrastructure, platform products, developer tooling, or foundational backend systems used by a large number of users
- Experience working on the infrastructure and framework layers behind AI systems such as agent orchestration, model-serving abstractions, evaluation systems, retrieval infrastructure, prompt/context tooling, MCP/A2A stack, platform APIs for AI development, etc
- Care deeply about developer experience and know how to design systems, interfaces, and abstractions that engineers actually want to use
- Strong distributed systems and backend engineering skills, highly effective in Python and/or TypeScript, and comfortable designing resilient services, APIs, asynchronous systems, and distributed workflows
- Designed robust, typed, well-structured interfaces such as REST, gRPC, SDKs, or platform contracts that support long-term extensibility and adoption
- Understand how frameworks like LangChain, LangGraph or LlamaIndex work under the hood and know when to abstract them away, having built frameworks using them to solve various AI concerns for developers
- Understand latency, throughput, reliability, token/cost management, model-provider integration, and the realities of running AI systems in production
- Built or contributed to tracing, quality measurement, automated evaluation, or other systems that help teams understand and improve AI system performance
- Know how to take repeated engineering problems and turn them into reusable golden paths, shared components, and organizational standards
- Familiarity with Kubernetes, Docker, and Terraform
- Intermediate to Expert level proficiency with TypeScript/JavaScript, React, and other web technologies
- Bachelor's Degree in Computer Science, Engineering, or a related field (or equivalent practical experience). An advanced degree (Master's or Ph.D.) is a strong plus
- Experience with agent frameworks and orchestration runtimes such as LangGraph, LangChain, LiveKit or similar systems
- Experience with model gateways, inference infrastructure, or provider-routing layers
- Experience with retrieval systems, vector databases, and context-management infrastructure
- Familiarity with MCP-style interfaces, tool interoperability patterns, or workflow schemas
- Experience with multi-tenant platform design, governance, or enterprise-grade controls
- Experience creating reference implementations, templates, or internal developer platforms
Benefits
- Flexible Time Off – We encourage a healthy work-life balance. Our flexible paid time off policy allows you to recharge and take time away as needed.
- Paid Holidays – Invoca provides 16 U.S. paid holidays, including a winter break, giving you ample opportunity to refresh and spend time with friends and family.
- Health Benefits – Our healthcare program includes medical, dental, and vision coverage, with multiple plan options so you can choose what works best for you and your family. Fertility assistance is also included.
- Retirement – Invoca offers a 401(k) plan through Fidelity with a company match of up to 4%.
- Stock Options – All employees are invited to share in Invoca’s success through stock options.
- Mental Health Program– Well-being support on a broad range of issues is available through our SpringHealth program.
- Paid Family Leave – Up to 6 weeks of 100% paid leave is provided for baby bonding, adoption, and caring for family members.
- Paid Medical Leave – Up to 12 weeks of 100% paid leave is provided for childbirth and medical needs.
- InVacation – As a thank-you to our long-term team members, we offer a bonus after 7 years of service.
- Wellness Subsidy – We provide a subsidy that can be applied toward gym memberships, fitness classes, and more.
Company Overview
Invoca, the recognized leader in conversation intelligence AI for marketing, e-commerce, and contact center teams It was founded in 2008, and is headquartered in Santa Barbara, California, USA, with a workforce of 201-500 employees. Its website is http://www.invoca.com.