Senior AI Engineer
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Job Location:
Monthly Salary:
Posted on:
11 hours ago
Vacancies:
1 Vacancy
Job Summary
About Workato
Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration Workato helps businesses globally streamline operations by connecting data processes applications and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time driving efficiency and agility.
Trusted by a community of 400000 global customers Workato empowers organizations of every size to unlock new value and lead in todays fast-changing world. Learn how Workato helps businesses of all sizes achieve more at .
Why join us
Ultimately Workato believes in fostering a flexible trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.
But we also believe in balancing productivity with self-care. Thats why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
If this sounds right up your alley please submit an application. We look forward to getting to know you!
Also feel free to check out why:
Business Insider named us an enterprise startup to bet your career on
Forbes Cloud 100 recognized us as one of the top 100 private cloud companies in the world
Quartz ranked us the #1 best company for remote workers
Responsibilities
Were building an AI platform that powers intelligent automation agentic workflows and large-scale retrieval services across our enterprise. Looking for an engineer who understands both the systems layer and the AI protocol layer.
Design and develop production-grade AI services and APIs that integrate with multiple LLM providers (OpenAI Anthropic open-source models). Build the core infrastructure not just applications on top of it.
Create an enterprise-grade agentic framework for orchestration retrieval and collaboration between multiple AI agents. This means understanding how agents communicate how to handle state how to route requests efficiently.
Implement knowledge retrieval systems and semantic search using vector databases (Qdrant ElasticSearch). Youll work on the actual retrieval logic and optimization not just plugging in a vector DB.
Build shared Python libraries and SDKs used across multiple services. Write code that other engineers will depend on which means it needs to be clean well-tested and properly documented.
Drive observability and validation for AI systems. Build monitoring that actually tells you whats happening with model performance latency cache hit rates and failure modes.
Requirements
Qualifications / Experience / Technical Skills
Youve built production services with proper observability deployment pipelines monitoring and security. You know how to run reliable systems at scale handle data-intensive workloads and debug distributed systems when things break.
You understand how things work under the hood. Standard libraries over frameworks. You can read a protocol spec and implement against it directly. When you need to integrate with an API you understand whats happening on the wire.
Senior-level experience in Go or Python (5 years in one comfortable in the other). If youre coming from Go you should know Python well enough to work in it for the first few quarters and vice versa. Youll be writing Python for core platform work.
Strong grasp of distributed systems API design and data-driven architectures. Youve worked with both relational and non-relational databases (PostgreSQL Elastic vector databases).
AI/LLM Experience
Youve worked with LLMs at the protocol level. You understand message structures caching strategies tool calling mechanics and streaming responses. You know whats happening during inference not just what the SDK abstracts away.
Youve integrated with OpenAI-compatible APIs ideally building directly against the protocol rather than relying on high-level frameworks. You can evaluate an LLM response understand token usage and optimize for latency and cost.
Experience with semantic retrieval vector databases or knowledge graph architectures is valuable. You understand the tradeoffs between different retrieval strategies.
Working Style
You learn fast and stay current. You monitor whats happening in AI infrastructure globally and can evaluate new approaches quickly.
You participate in technical design discussions code reviews and mentor other engineers. You can explain complex technical concepts clearly to both engineers and non-technical stakeholders.
Youre comfortable with the full development lifecycle: design implementation deployment monitoring and continuous improvement.
Environment
Youll work with Python FastAPI LLM APIs vector databases PostgreSQL Kubernetes and modern CI/CD tooling. We use frameworks where appropriate (LiteLLM Langfuse etc.) but prefer engineers who understand whats underneath and can work at the protocol level when needed.
To stand out in our hiring process please take the time to respond to the Job Application Questions below with concise yet informative answers. All submissions are personally reviewed by the Hiring Team not evaluated by AI.
Job Req ID: 2406
Required Experience:
Senior IC
Key Skills
- APIs
- C/C++
- Computer Graphics
- Go
- React
- Redux
- Node.js
- AWS
- Library Services
- Assembly
- GraphQL
- High Voltage
About Company
A single platform to orchestrate data integration, app connectivity, and process automation across your organization.
