About Seeq
Seeq builds advanced analytics software for customers in process manufacturing industries such as pharmaceuticals, mining, renewables, and energy — organizations with massive amounts of time-series and event data from industrial operations.
We are a fully remote company that has operated this way from the start, using tools like Zoom, Slack, and our homegrown Qube virtual office to collaborate as if we were in the same building. Our teams iterate using agile practices and care deeply about clear communication, shared learning, and delivering software that exceeds customer expectations.
Role Overview
The AI Software Engineer is a domain-leading individual contributor who helps define and scale the backend platforms and AI systems supporting Seeq’s intelligent applications.
You will own highly ambiguous, cross-team technical initiatives and provide architectural leadership for backend platforms and agentic systems, helping establish the shared infrastructure, services, APIs, and engineering patterns that allow AI-enabled capabilities to operate reliably and safely at scale across Seeq.
This is a deeply hands-on role. You will combine significant experience building AI systems with strong backend and distributed systems expertise, broad technical influence, and continued involvement in designing, coding, debugging, and shipping production software.
Key Responsibilities
- Set technical direction for backend and AI platform capabilities: Define architecture, patterns, and technical approaches for scalable systems supporting AI and agentic applications.
- Lead high-impact AI and platform initiatives: Own complex, ambiguous projects from concept through production, coordinating work across engineers, teams, and stakeholders.
- Architect agentic systems: Design and build systems supporting agent routing, orchestration, tool use, evaluations, runtime infrastructure, sandboxing, and agent-to-agent communication.
- Build and evolve shared platform infrastructure: Define backend services, runtime environments, interfaces, and architectural patterns that other engineering teams rely on to build AI-enabled applications.
- Build reliable distributed and data-intensive systems: Develop backend services and APIs capable of supporting AI workloads across large data volumes and complex workflows.
- Create reusable AI platform capabilities: Build shared services, APIs, libraries, orchestration patterns, runtime infrastructure, and developer-facing platform capabilities that enable multiple teams to build, deploy, and operate AI features consistently.
- Drive AI evaluation and reliability: Establish approaches for evaluating agentic output, monitoring system behavior, and improving the reliability, safety, and observability of AI-enabled systems.
- Design systems integrations: Build integrations that allow AI agents, internal services, and third-party enterprise platforms to communicate effectively.
- Drive work from idea to production: Evaluate emerging approaches and translate promising AI technologies and patterns into pragmatic, maintainable production systems.
- Stay close to customers: Work directly with customers during early deployments, understand how AI-enabled capabilities perform in real-world environments, and incorporate those learnings back into the product.
- Mentor and grow engineers: Provide technical mentorship in backend architecture, platform engineering, agentic systems, AI engineering, and operational excellence.
- Identify opportunities proactively: Surface risks, challenge assumptions, and identify better technical approaches rather than waiting for problems or solutions to be fully defined.
- Collaborate with product managers and owners to develop and hone a vision for how generative AI is used by analytics engineering teams.
Requirements
Required:
- Minimum 10+ years of professional software engineering experience, including experience operating at Staff or equivalent scope
- A substantial portion of recent experience focused on generative AI or agentic systems
- Proven track record leading complex AI, agentic, or platform initiatives from concept through production
- Extensive hands-on experience building and operating agentic systems, including areas such as agents, routing/orchestration, tool use, evaluations, runtimes, sandboxing, or related infrastructure
- Deep expertise in Python and backend engineering, including designing large-scale distributed systems, services, APIs, and data-intensive workflows
- Experience designing or owning shared platform services or infrastructure used by multiple engineering teams, including APIs, runtime systems, orchestration, deployment infrastructure, or common backend services
- Experience with modern AI/LLM frameworks, SDKs, or orchestration tooling used to build production AI and agentic applications
- Experience developing evaluation strategies and observability for AI or agentic systems
- Familiarity with SQL and experience with relational databases such as PostgreSQL
- Experience deploying and operating production systems in Kubernetes or another containerized runtime environment
- Experience building and operating software in a SaaS environment
- Strong understanding of production AI concerns including reliability, monitoring, performance, cost, and failure handling
- Ability to evaluate emerging AI approaches and translate them into pragmatic, maintainable software
- Demonstrated ability to take ownership of ambiguous technical problems and independently drive them forward
- Proven technical leadership of engineers and teams while maintaining strong individual hands-on contribution
- Strong communication skills and experience mentoring and coaching engineers
Preferred:
- Experience architecting multi-agent or complex agentic platforms used across multiple teams or products
- Experience defining shared AI or backend platform capabilities used broadly across an engineering organization
- Experience with retrieval architectures such as vector search, hybrid retrieval, re-ranking, or RAG
- Experience integrating AI agents with third-party enterprise platforms
- Experience working with industrial, operational, or time-series data
- Experience building software products used by technical or engineering-focused customers
- A background in mechanical, chemical, process, or another engineering discipline before moving into software
Benefits
Seeq is a remote-first (and only) company founded by serial entrepreneurs. Our executive team and board of directors have extensive experience with successful startup ventures in high-growth environments.
We are founded on the idea that companies need better solutions for quickly and easily getting business insight from their industrial process data. Our mission is to provide software and services that convert that data into meaningful information that the business can use to improve profitability and sustainability.
We have a wonderful, kind-hearted, talented team that loves to collaborate, lead by example, and exceed our customers’ expectations. We are certified as a great place to work, and included in the Technology Fast 500 and Inc. Magazine’s Best Places to Work.
The Perks of Working at Seeq
- Competitive salary, equity, and cash bonus incentives
- Benefits:
- Unlimited PTO
- Internet and mobile phone reimbursements
- Annual company meetups
- 4-week paid sabbatical every 7 years at Seeq
- Vacation bonus program
- Generous home office allowance
- The best co-workers (we've analyzed the data, so we know it's true.)
- Pet-friendly workspace (your dog will be so happy to have you home)
- A job you'll love!
Seeq provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics.
You must be authorized to work in the country in which you reside. Seeq does not sponsor US F1 or H-1B work visas