Senior Software Engineer, Agentic Platforms
The Senior Software Engineer at Confidential Client will design and operate robust distributed systems and platform services that enable AI engineering workflows. This role focuses on building an agentic layer to connect agents with engineering decisions, automating manual workflows, and collaborating directly with customers to drive adoption and improve platform capabilities. The position offers the opportunity to work on cutting-edge AI and autonomous driving technologies within a leading smart technology company.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Motor Vehicle Manufacturing.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
About the Role
You will be a senior engineer building an internal AI engineering platform used by engineers across the organization. The mission is to create platform services, reliable pipelines, and automation that connect agentic capabilities (natural-language intake, task orchestration, multi-agent workflows) to real engineering systems and decisions. The role combines strong software engineering, distributed-systems design, and pragmatic product-facing work with internal customers to drive adoption and safe automation.
What You’ll Do
- Design, build, and operate production-grade platform services and infrastructure with strong reliability, observability, and performance.
- Identify manual, repetitive engineering workflows and eliminate them through self-service automation on the platform.
- Build and evolve the agentic layer: agent lifecycle, tool integrations, sandboxed execution, and multi-agent workflows.
- Design a semantic data layer that models systems, workflows, and decision data as connected objects agents can query and act on.
- Build safe action execution paths: connectors to operational systems, staged propose–validate–approve–commit flows, with granular access control and end-to-end decision lineage/audit.
- Own system design for new platform capabilities end to end, from requirements through rollout and operations.
- Work directly with internal customers: lead technical onboarding, gather requirements, debug production issues, and turn field feedback into roadmap priorities.
- Establish best practices for agent evaluation, observability, and safety guardrails.
Minimum Qualifications
- Master’s degree in Computer Science, Software Engineering, or a related field.
- 5+ years building and operating production distributed systems with demonstrated strength in system design and software engineering fundamentals.
- Proficiency in Python and TypeScript; solid experience with databases, message queues, caching, and API design.
- A builder’s instinct for automation with a track record of turning manual processes into tools, pipelines, or self‑service systems.
- Hands-on experience with modern AI tooling and LLM APIs, including tool use and function-calling patterns.
- Experience with agentic systems or task orchestration platforms (workflow engines, multi-agent frameworks, MCP-style servers, or similar).
- Strong cross-team communication and customer-facing skills.
Preferred Qualifications
- Familiarity with autonomous driving terminology and model development workflows.
- Direct customer-facing experience (solutions engineering, technical onboarding, developer relations, or enterprise support).
- Experience with data/domain modeling: semantic layers, knowledge graphs, or object models over heterogeneous data sources.
- Experience integrating with enterprise or operational systems (internal platforms, legacy APIs, and write-back to systems of record).
- Experience with evaluation frameworks and observability for LLM-powered applications.
- Familiarity with sandboxing/isolation technologies and secure execution environments.
- Contributions to open-source agent frameworks, MCP servers, or developer tools.
- Experience driving developer tooling adoption within engineering organizations.
Compensation & Benefits
The base salary range for this full-time position is $174,720 - $295,680, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and work location. Within the range, individual pay is determined by job-related skills, experience, and relevant education or training.
- Competitive compensation package (base + bonus + equity).
- Benefits and wellness programs.
- Opportunity to work on cutting-edge AI and agentic systems within the transportation / motor-vehicle manufacturing industry.
- Collaborative, supportive engineering culture with snacks, lunches, and team activities.
Workplace & Process Notes
- Employment type: Full-time.
- Location: Santa Clara, CA (on-site or hybrid per client policy—confirm details during interview).
- This role involves direct collaboration with engineering teams, product stakeholders, and internal customers to drive platform adoption and operational excellence.
- The hiring process will assess system design, distributed systems experience, coding ability in Python/TypeScript, and practical experience building automation and agentic integrations.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
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