Staff Agentic Artificial Intelligence Engineer

Overview

Principal-level (P4) technical leadership role within Trimble's Construction Management Solutions team in Chennai, defining enterprise AI/ML infrastructure strategy and MLOps practices across business units.

What you'll do

• Define the multi-year technical roadmap for enterprise AI/ML infrastructure, architecting unified platforms serving thousands of models with sub-second latency across diverse business units.
• Implement advanced MLOps solutions, including automated hyperparameter optimization, neural architecture search (NAS), model quantization, and distributed serving architectures supporting millions of predictions.
• Architect scalable infrastructure for emerging generative technologies, including Large Language Models (LLMs), multi-modal systems, prompt-engineering pipelines, and federated learning frameworks.
• Engineer comprehensive ML observability stacks featuring custom telemetry, drift detection, automated anomaly mitigation, Zero Trust architectures, and model privacy preservation.
• Establish cross-organizational MLOps governance, compliance standards, and A/B or multi-armed bandit experimentation frameworks across multiple engineering hubs.
• Partner directly with C-suite leadership and product executives to align technology investments with business outcomes.
• Represent Trimble through patents, publications, and open-source contributions.

What you'll need

• Advanced degree (Master's or PhD) in Computer Science, Machine Learning, Engineering, or a related technical discipline, or equivalent professional experience with exceptional technical depth.
• 8+ years of dedicated experience in MLOps, Machine Learning Engineering, or Site Reliability Engineering (SRE).
• At least 3+ years operating in senior/principal technical leadership capacities.
• Proven track record architecting and maintaining large-scale ML infrastructure serving millions of daily predictions with high availability and extreme fault tolerance.
• Expert programming capabilities across multiple modern languages (Python, Go, Rust, Java, or C++) with deep expertise in distributed computing, concurrency, and performance tuning.
• Extensive experience architecting cloud solutions across AWS, Azure, or GCP, leveraging advanced AI/ML managed services while enforcing rigorous FinOps cost optimization.
• Deep expertise managing end-to-end ML lifecycles at scale, including automated experimentation, feature stores, model registries, and sophisticated rollout frameworks.
• Practical mastery of advanced cloud-native infrastructure including Kubernetes, service mesh architectures (e.g., Istio), event-driven streaming (Kafka), and serverless ML pipelines.

Nice to have

• Direct experience operationalizing transformer architectures, foundation model fine-tuning (LoRA, QLoRA), and enterprise-grade vector database retrieval infrastructure.
• Familiarity with real-time streaming pipelines, Data Mesh paradigms, and privacy-preserving data analytics.
• In-depth knowledge of model explainability/interpretability frameworks, bias mitigation tools, and regulatory guidelines (GDPR, CCPA, EU AI Act).
• Published academic research, registered patents, or prominent contributions to open-source MLOps toolkits.
• Familiarity with neuromorphic hardware, specialized AI accelerators (TPUs/NPUs), or quantum computing paradigms.

Details

• Location: Chennai, India (Chennai engineering hub).
• Full-time position.
• Flexible work arrangements offered.