AI Efficiency Architect (Intelligent R&D Productivity Expert)_BCSC

Responsibilities

• Productivity Architecture & Roadmap
• Analyze the full software development lifecycle (requirements → modeling → coding → testing → integration → calibration) for ADAS and Chassis/Powertrain domains. Identify high-effort, low-cognitive, standardizable daily tasks.
• Design a two-tier "AI Agent + Skill" architecture: define Skill granularity, I/O standards, and fallback mechanisms; design agent decision-making and orchestration logic.
• Create a phased roadmap with measurable goals (e.g., 30% reduction in time for test case generation, 2x faster calibration data analysis) and visible gains within 3-6 months.
• Skillization & Scenario Implementation
• Convert typical engineering actions into AI-callable Skills, for example:
• Automatically parse ADAS scenario requirements → generate test cases
• Chassis controller change impact analysis → auto-update interface docs + unit test stubs
• Anomaly pattern detection in calibration data → produce diagnostic report
• Build and maintain a Skill repository to enable reuse and reduce onboarding costs for business teams.
• Agentic Workflow Development
• Orchestrate multi-agent collaboration: e.g., "Requirements Change Agent → Impact Analysis Agent → Auto Test Agent → Regression Verification Agent"
• Enable Agents to call the existing toolchain (Jira, Git, Matlab/Simulink, Vector tools, Jenkins, etc.)
• Design a human-in-the-loop interface: critical decisions require manual approval; routine tasks run fully automatically.
• Business Alignment & Adoption
• Work closely with UAES ADAS, Chassis & Powertrain development teams to understand real pain points under AUTOSAR, ISO 26262, ASPICE.
• Collaborate with functional safety and quality teams to ensure traceability and compliance of AI-generated artifacts (code, test cases, reports).
• Train engineers on using AI productivity tools, collect feedback, and iterate on Skills.
• Must-Have Experience
• 5+ years in software development or R&D productivity, with at least 2 years focused on AI-powered engineering (e.g., code generation, auto test generation, defect prediction).
• Familiar with ADAS or Chassis/Powertrain embedded software development processes. Experience with UAES or similar Tier-1 suppliers is a strong plus.
• Proven track record of delivering AI Agent / Copilot / workflow automation projects (beyond just API calls), with measurable efficiency improvements.
• Technical Skills
• Solid understanding of LLMs (GPT-4, Claude, DeepSeek, etc.) and their application patterns: prompt engineering, RAG, function calling, multi-agent frameworks (LangChain, Semantic Kernel, or similar).
• Basic to intermediate programming (Python/Java) - able to write Skill adapters and orchestration scripts.
• Familiarity with at least two embedded development tools: Simulink, CANoe, Davinci, Trace32, etc.
• Plus: Knowledge of ASPICE, ISO 26262, AUTOSAR architecture.
• Core Mindset
• Engineering mindset: ability to turn vague "efficiency ideas" into measurable, implementable Skills.
• Business-driven: focus on solving real, tedious pain points for ADAS/chassis engineers - no tech for tech's sake.
• Persuasive & coaching ability: willing to change team habits, backed by data.

Additional Information

Role Overview You will define and drive the AI-driven efficiency program for software development at BCSC. The core goal is to replace repetitive, rule-based daily tasks with AI Agents + Skills - specifically within Truck ADAS, Chassis & Powertrain embedded software development. You will start with the overall productivity architecture, identify automatable workflows, gradually break business logic into executable "Skills," and orchestrate Agentic workflows, ultimately achieving a step-change in R&D efficiency.

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