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Salary: USD 170,000 - 205,000 / annual
Seeq builds advanced analytics software for process manufacturing industries—pharmaceuticals, mining, renewables, energy—helping organizations extract insights from massive amounts of time-series and operational data. The company is fully remote-first and operates with agile practices emphasizing clear communication and customer-focused delivery.
The AI Software Engineer is a domain-leading individual contributor and Staff/Principal-level role responsible for defining and scaling backend platforms and AI systems that power Seeq's intelligent applications. This is a deeply hands-on position combining significant AI systems experience with strong backend and distributed systems expertise, broad technical influence, and continued involvement in designing, coding, debugging, and shipping production software.
Key responsibilities include:
- Setting technical direction for backend and AI platform capabilities, defining architecture and patterns for scalable systems supporting AI and agentic applications
- Leading high-impact AI and platform initiatives from concept through production, coordinating across engineers, teams, and stakeholders
- Architecting agentic systems including agent routing, orchestration, tool use, evaluations, runtime infrastructure, sandboxing, and agent-to-agent communication
- Building and evolving shared platform infrastructure—backend services, runtime environments, interfaces, and architectural patterns that other teams depend on
- Developing reliable distributed and data-intensive systems capable of supporting AI workloads across large data volumes and complex workflows
- Creating reusable AI platform capabilities including shared services, APIs, libraries, orchestration patterns, and developer-facing infrastructure
- Driving AI evaluation and reliability by establishing approaches for evaluating agentic output, monitoring system behavior, and improving safety and observability
- Designing systems integrations allowing AI agents, internal services, and third-party enterprise platforms to communicate effectively
- Translating emerging AI technologies and patterns into pragmatic, maintainable production systems
- Working directly with customers during early deployments to understand real-world performance and incorporate learnings back into the product
- Mentoring and growing engineers in backend architecture, platform engineering, agentic systems, and operational excellence
- Proactively identifying opportunities, surfacing risks, challenging assumptions, and proposing better technical approaches
- Collaborating with product managers to develop vision for how generative AI serves analytics engineering teams
Requirements:
- Minimum 10+ years of professional software engineering experience, including Staff or equivalent scope
- Substantial 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 (agents, routing/orchestration, tool use, evaluations, runtimes, sandboxing, infrastructure)
- Deep expertise in Python and backend engineering, including large-scale distributed systems, services, APIs, and data-intensive workflows
- Experience designing or owning shared platform services or infrastructure used by multiple engineering teams (APIs, runtime systems, orchestration, deployment infrastructure, backend services)
- Experience with modern AI/LLM frameworks, SDKs, or orchestration tooling for production AI and agentic applications
- Experience developing evaluation strategies and observability for AI or agentic systems
- Familiarity with SQL and relational databases such as PostgreSQL
- Experience deploying and operating production systems in Kubernetes or containerized runtime environments
- Experience building and operating software in a SaaS environment
- Strong understanding of production AI concerns: reliability, monitoring, performance, cost, 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 drive them forward independently
- 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 (vector search, hybrid retrieval, re-ranking, 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
- Background in mechanical, chemical, process, or another engineering discipline before transitioning to software
